August 2021 - cypherpunks - lists.cpunks.org

Libertarianism - the stink-bomb of politics
by professor rat 13 Aug '21

13 Aug '21

https://theworld.com/~mhuben/libindex.html Marxism of the Right = NAZBOL

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You're Doing IoT RNG
by coderman 13 Aug '21

13 Aug '21

https://labs.bishopfox.com/tech-blog/youre-doing-iot-rng You're Doing IoT RNG [Dan Petro](https://labs.bishopfox.com/authors/dan-petro) [Allan Cecil](https://labs.bishopfox.com/authors/allan-cecil) on Aug 5, 2021 11:43:40 AM There’s a crack in the foundation of Internet of Things (IoT) security, one that affects [35 billion devices worldwide](https://findstack.com/internet-of-things-statistics/). Basically, every IoT device with a hardware random number generator (RNG) contains a serious vulnerability whereby it fails to properly generate random numbers, which undermines security for any upstream use. See Dan and Allan discuss their research at DEF CON 29: --------------------------------------------------------------- In order to perform most security-relevant operations, computers need to generate secrets via an RNG. These secrets then form the basis of cryptography, access controls, authentication, and more. The details of exactly how and why these secrets are generated varies for each use, but the canonical example is generating an encryption key: FIGURE 1: Alice and Bob trying to have a private conversation using RNG In order for Alice and Bob to communicate secretly, away from the prying eyes of Eve, they need to produce a shared secret by using an RNG. The fact that Eve does not know this number is the only thing keeping her from compromising the secrecy of the communications. This same story plays out for other aspects of security: whether it’s SSH keys for authentication or session tokens for authorization, random numbers are one of the bedrock foundations of computer security. But it turns out that these “randomly” chosen numbers aren’t always as random as you’d like when it comes to IoT devices. In fact, in many cases, devices are choosing encryption keys of 0 or worse. This can lead to a catastrophic collapse of security for any upstream use. As of 2021, most new IoT systems-on-a-chip (SoCs) have a dedicated hardware RNG peripheral that’s designed to solve exactly this problem. But unfortunately, it’s not that simple. How you use the peripheral is critically important, and the current state of the art in IoT can only be aptly described as “doing it wrong.” INCORRECTLY CALLING THE HARDWARE RNG One of the more glaring pitfalls happens when developers fail to check error code responses, which often results in numbers that are decidedly less random than required for a security-relevant use. When an IoT device requires a random number, it makes a call to the dedicated hardware RNG either through the device’s SDK or increasingly through an IoT operating system. What the function call is named varies, of course, but it takes place in the hardware abstraction layer (HAL). This is an API created by the device manufacturer and is designed so you can more easily interface with the hardware through C code and not need to mess around with setting and checking specific registers unique to the device. The HAL function looks something like this: u8 hal_get_random_number ( u32 * out_number ) ; There are two parts that we care about: - An output parameter called out_number. This is where the function will put the random number; it’s a pointer to an unsigned 32-bit integer. - A return value to specify any error cases. Depending on the device, it could be Boolean or any number of enumerated error conditions. So, the first question you might be asking is, “How many people out there in the wild actually check this error code?” Unfortunately, the answer is almost nobody. For instance, just look at GitHub results for use of the MediaTek 7697 SoC HAL function: https://github.com/search?p=1&q=hal_trng_get_generated_random_number&type=C… Or even FreeRTOS’s (a popular IoT operating system) abstraction layer: https://github.com/search?q=HAL_RNG_GenerateRandomNumber&type=code Notice that the return code is pervasively not checked – though this isn’t unique to these two examples. This is just how the IoT industry does it. You’ll find this behavior across basically every SDK and IoT OS. WHAT'S THE WORST THAT COULD HAPPEN? Okay, so devices aren’t checking the error code of the RNG HAL function. But how bad is it really? It depends on the specific device, but potentially bad. Very bad. Let’s take a look. The HAL function to the RNG peripheral can fail for a variety of reasons, but by far the most common (and exploitable) is that the device has run out of entropy. Hardware RNG peripherals pull entropy out of the universe through a variety of means (such as analog sensors or EMF readings) but don’t have it in infinite supply. They’re only capable of producing so many random bits per second. If you try calling the RNG HAL function when it doesn’t have any random numbers to give you, it will fail and return an error code. Thus, if the device tries to get too many random numbers too quickly, the calls will begin to fail. But that’s the thing about random numbers; it’s not enough to just have one. When a device needs to generate a new 2048-bit private key, as a conservative example, it will call the RNG HAL function over and over in a loop. This starts to seriously tax the hardware’s ability to keep up, and in practice, they often can’t. The first few calls may succeed, but they will typically start to cause errors quickly. So… what does the HAL function actually give you for a random number when it fails? Depending on the hardware, one of the following: - Partial entropy - The number 0 - Uninitialized memory FIGURE 2: That shouldn’t be there. None of those are very good, but uninitialized memory?! How does that happen? Well, recall that the random number is an output pointer. Then consider the following pseudocode (which you can find many examples of on GitHub if you care to look): u32 random_number ; hal_get_random_number ( & random_number ) ; // Sends over the network packet_send ( random_number ) ; The random_number variable is declared and lives on the stack but is never initialized. If the HAL function behaves such that it never overwrites the output variable in the event of an error (which is common behavior), then the value in the variable will contain uninitialized RAM. Which we then send out over the network to someone else. Not great. These are not contrived or unrealistic scenarios. Devices are out there right now using crypto keys of 0 or worse. An analysis by [Keyfactor](https://www.keyfactor.com/resources/factoring-rsa-keys-in-the-io… back in 2019 of publicly available RSA certificates found that 1 in 172 of all certificates are vulnerable to known attacks. The authors pointed to random number generation in IoT devices as being one of the culprits, but stopped short of identifying the exact cause. While we can't say for sure that our research is responsible for those results... widespread instances of weak RSA keys in IoT devices is exactly what you'd expect to find. It sure seems like this is an exploitable large scale issue in practice, not just in theory. DON'T BLAME THE USER It’s easy to look at the current state of affairs and conclude that it’s simply user error, but this is not the case. The users have been put in a no-win situation. You see, random numbers are incredibly critical when you need them. Oftentimes you can’t just “handle” the error in an elegant way and move forward. For example, the MediaTek documentation contains the following example code for developers of the MT7697 SoC: if ( HAL_TRNG_STATUS_OK != hal_trng_get_generated_random_number ( & random_number ) ) { //error handle } But if you’re the networking stack in the middle of generating a crypto key for secure communications, how are you supposed to “handle” the error? There are really only two options: - Abort, killing the entire process. - Spin loop on the HAL function for an indefinite amount of time until the call completes, blocking all other processes and using 100% CPU in the process. Neither are acceptable solutions. This is why developers ignore the error condition — the alternatives are terrible and the ecosystem around RNG hardware has done them no favors. Things aren’t much better even when developers have the benefit of time on their side. Some devices, like the STM32, have sizable documentation and even vendor-provided proof of randomness whitepapers, but these are an exception. Few devices have even a basic description of how the hardware RNG is supposed to work, and fewer still have any kind of documentation about basic things like expected operating speed, safe operating temperature ranges, and statistical evidence of randomness. Anecdotally speaking, we attempted to follow the STM32 documentation carefully and still managed to create code that incorrectly handled error responses. It took multiple attempts and substantial code to block additional calls to the RNG and spin loop properly when there were error responses — and even then, we observed questionable results that made us doubt our code. It’s no wonder developers are doing IoT RNG, well, wrong, but more on that below. CSPRNG SUBSYSTEM So you might be wondering, “What makes this unique to the IoT? Does this issue affect laptops and servers too?” The answer is that it’s a unique issue to the IoT world because this sort of low-level device management is usually handled by an operating system that’s notably missing from typical IoT devices. FIGURE 3: CSPRNG subsystem components When an application needs a cryptographically secure random number on a Linux server, it doesn’t read from the hardware RNG directly or make a call to some HAL function and fight with error codes. No, it just reads from /dev/urandom. This is a cryptographically secure pseudo-random number generator (CSPRNG) subsystem made available to applications as an API. There are similar subsystems on every major operating system, too: Windows, iOS, MacOS, Android, BSD, you name it. Importantly, calls to /dev/urandom never fail and never block program execution. The CSPRNG subsystem can produce an endless sequence of strong random numbers immediately. This squarely solves the problem of HAL functions that either block program execution or fail. Another critical design feature of a CSPRNG subsystem is the entropy pool. This is designed to take in entropy from a variety of sources, hardware RNGs (HWRNGs) included. Due to the magic of the xor operation, all of these individually weak sources of entropy can be combined into one strong one. The entropy pool also removes any single points of failure among the entropy sources: in order to break the RNG, you’d need to predict every entropy source simultaneously. This is the right way to generate cryptographically secure random numbers and is already industry standard everywhere … except the IoT. --------------------------------------------------------------- Why you really do need a CSPRNG Subsystem Designing an entire CSPRNG subsystem sounds really hard, especially when your gadget isn’t using one of those new IoT operating systems. Maybe it’s enough to just bite the bullet and spin loop on the RNG HAL function. That way you’re always getting good random numbers, right? This section will disavow you of the idea that hardware RNGs are safe to use on their own. VULNERABLE REFERENCE CODE Nobody writes source code entirely from scratch, especially in the world of IoT devices. There’s always some reference code or example doc that developers start from. Interfacing with hardware is tricky to get right for any device, let alone one as finicky as a hardware RNG peripheral. When the device’s reference code contains a vulnerability, it propagates down to every device using it. After all, how is a developer supposed to know the difference between a vulnerable reference implementation and a quirky one? Here are some examples: Using the HWRNG to Seed an Insecure PRNG PRNGs such as libc rand() are wildly insecure since the numbers they produce reveal information about the internal state of the RNG. They’re fine for non-security-relevant contexts because they’re fast and easy to implement. But using them for things like encryption keys leads to catastrophic collapse of the device’s security, as all of the numbers are predictable. Unfortunately, many SDKs and operating systems that support hardware RNGs use an insecure PRNG under the hood. The Contiki-ng IoT operating system for Nordic Semiconductor’s nrf52840 SoC does precisely this by seeding the insecure libc rand() function with the hardware RNG:: https://contiki-ng.readthedocs.io/en/release-v4.6/_api/arch_2cpu_2nrf52840_… void random_init ( unsigned short seed ) { ( void ) seed ; unsigned short hwrng = 0 ; NRF_RNG -> TASKS_START = 1 ; NRF_RNG -> EVENTS_VALRDY = 0 ; while ( ! NRF_RNG -> EVENTS_VALRDY ) ; hwrng = ( NRF_RNG -> VALUE & 0xFF ) ; NRF_RNG -> EVENTS_VALRDY = 0 ; while ( ! NRF_RNG -> EVENTS_VALRDY ) ; hwrng |= ( ( NRF_RNG -> VALUE & 0xFF ) & lt ; & lt ; 8 ) ; NRF_RNG -> TASKS_STOP = 1 ; srand ( hwrng ) ; } FIGURE 4: Seeding libc rand() with the hardware RNG entropy unsigned short random_rand ( void ) { return ( unsigned short ) rand ( ) ; } FIGURE 5: Future calls to random_rand() call the insecure libc rand() To be clear, there is NO secure way to use libc rand() to generate secure values. The fact that the seed is created using the hardware is irrelevant since an attacker can just derive or enumerate it using [untwister](https://github.com/bishopfox/untwister). What’s important is that when the user calls random_rand(), the output will come from the insecure libc rand() call. You can also see identical vulnerable behavior in the MediaTek Arduino code: https://github.com/MediaTek-Labs/Arduino-Add-On-for-LinkIt-SDK/blob/53acd43… /** * @brief This function is to get random seed. * @param[in] None. * @return None. */ static void _main_sys_random_init ( void ) { # if defined ( HAL_TRNG_MODULE_ENABLED ) uint32_t seed ; hal_trng_status_t s ; s = hal_trng_init ( ) ; if ( s == HAL_TRNG_STATUS_OK ) { s = hal_trng_get_generated_random_number ( & seed ) ; } if ( s == HAL_TRNG_STATUS_OK ) { srand ( ( unsigned int ) seed ) ; } FIGURE 6: Insecure libc rand() usage in MediaTek SDK So even if your device has a hardware RNG peripheral, and even if you think that you’re using it, you might not be. Usage Quirks Sometimes, devices work in a very quirky way that is not at all immediately obvious. Failing to properly account for these quirks can lead to a catastrophic collapse of a device’s security. One example of this is the LPC 54628. When testing the LPC 54628, we noticed that we were getting extremely poor-quality random numbers from the hardware RNG — so bad that we suspected there might be something wrong with our tooling. Turns out we were right. If you read the user manual carefully, on page 1,106 (of 1,152), you’ll notice the following instructions: "The quality of randomness (entropy) of the numbers generated by the Random Number Generator relies on the initial states of internal logic. If a 128 bit or 256 bit random number is required, it is not recommended to concatenate several words of 32 bits to form the number. For example, if two 128 bit words are concatenated, the hardware RNG will not provide 2 times 128 bits of entropy. …omitted for brevity… To constitute one 128 bit number, a 32 bit random number is read, then the next 32 numbers are read but not used. The next 32 bit number is read and used and so on. Thus 32 32-bit random numbers are skipped between two 32-bit numbers that are used." So in order to actually use the RNG peripheral properly, you’re supposed to get a random number and then throw way the next 32. Then keep doing that in a loop! In our testing code, we were just calling the RNG HAL function and using the results…, which is a fairly sensible way to write code. How many people bother to read that user manual? Or even if they find the “correct” code that discards numbers, do they remove it because it seems unnecessary? Clearly, it’s unacceptable for security to rely on such behavior. Even if some developers get it right some of the time, having this kind of an API is guaranteed to produce vulnerable devices given a large enough audience. STATISTICAL ANALYSIS Okay, so suppose that you’ve gone through the trouble of auditing your device’s code to make sure that it’s actually using the hardware RNG, and you made sure to check any error conditions and spin until the device was ready, and you laboriously read through your device’s 1,000-page user manual to make sure you caught any quirks…. Surely you must be safe, right? Not even close. It turns out that the raw entropy of IoT hardware RNG peripherals varies wildly in quality. Most devices fail statistical analysis tests, which we will summarize below. But keep in mind that these results can often depend on the individual device itself, as small manufacturing defects (or the relative positions of Jupiter and Saturn for all we know) produce diverging results for even the same make and model of a device. MediaTek 7697 One of the things we tested for when analyzing entropy is the relative distribution of bytes produced by the RNG. In a perfect world, we should expect each byte to be equally likely, so the distribution of bytes ought to be a flat line (Modulo any minor random blips of course). But that’s not what we see for the MT7697: FIGURE 7: Histogram of the frequency of each byte 0 to 255 on the MediaTek 7697 SoC The diagram above is a histogram showing the relative frequency of each possible byte (0 -> 255) empirically measured from a MediaTek 7697 SoC’s hardware RNG. Note that sawtooth pattern: That’s definitely “not random”. There shouldn’t be patterns of any kind. How comfortable do you feel about using that directly as your crypto key? Nordic Semiconductor nrf52840 The Nordic Semiconductor nrf52840 SoC’s hardware RNG exhibited a repeating 12-bit pattern of 0x000, occurring every 0x50 bytes: FIGURE 8: Repeating 0x000 in the nrf52840 SoC The fact that this was 12 bytes, and not 8 or 16, was quite curious. We don’t have a great explanation for that, but likely depends on the internal workings of the black-box RNG hardware. STM32-L432KC Unfortunately, we don’t have a nice diagram to show you for this one, but here are the results from dieharder, an industry-standard statistical randomness testing tool: #=============================================================================# # dieharder version 3.31.1 Copyright 2003 Robert G. Brown # #=============================================================================# rng_name | filename |rands/second| file_input_raw|STM32L432randData.4gb.32768trans.fullblocking.bin| 1.72e+07 | #=============================================================================# test_name |ntup| tsamples |psamples| p-value |Assessment #=============================================================================# rgb_minimum_distance| 0| 10000| 1000|0.00000000| FAILED FIGURE 9: Sample of dieharder statistical analysis results for the STM32-L432KC SoC As you can see, this fails the dieharder “RGB Minimum Distance” test. What this test does is use the RNG to plot numbers randomly in a large grid and then calculate the smallest distance between any two points. This test is especially good at identifying subtle correlations between numbers, such as repeats. Failing this test likely indicates that the numbers produced by the RNG are not independent of each other or that they repeat in some way. While many hardware RNGs we tested seemed fine, such as the LPC54628 (with 32*32-bit discarding) and the ESP32, the only reasonable conclusion to make here is that raw entropy taken from the hardware RNG should not be trusted in isolation. The key-stretching and entropy pooling that a CSPRNG subsystem offers are fundamentally required to avoid doing IoT RNG. --------------------------------------------------------------- Conclusions One of the hard parts about this vulnerability is that it’s not a simple case of “you zigged where you should have zagged” that can be patched easily. In order to remediate this issue, a substantial and complex feature has to be engineered into the IoT device. - This affects the entire IoT industry. The core vulnerability here doesn’t lie in a single device’s SDK or in any particular SoC implementation. - The IoT needs a CSPRNG subsystem. This issue can’t be fixed by just changing the documentation and blaming users. The most elegant place for such a CSPRNG subsystem is in one of the increasingly popular IoT operating systems. If you’re designing a new device from scratch, we’d recommend implementing a CSPRNG in an operating system. - RNG code should be considered dangerous to write on your own, just like crypto code. It doesn’t matter how clever you are, never write your own code to interface with the RNG hardware. You will almost certainly get it wrong. You should instead use a CSPRNG subsystem made available by a lower abstraction layer. - Never use entropy directly from RNG hardware. Across the board, hardware RNGs are not suitable for (immediate) cryptographic use. Weak entropy can and should be fixed through software, via a CSPRNG. In the short term, here’s what you can do: DEVICE OWNERS Keep an eye out for updates and make sure to apply them when they become available. This is an issue that can be solved with software, but it may take some time. In the meantime, be careful about trusting your IoT gadgets too much. For home devices that require an internet connection, [place them in a dedicated network segment](https://labs.bishopfox.com/industry-blog/an-updated-guide-to-do-it… that can only reach out externally. This will help contain any breach from spreading to the rest of your network. IOT DEVICE DEVELOPERS If possible, select IoT devices that include a CSPRNG API seeded from a variety of entropy sources including hardware RNG’s. If there’s no CSPRNG available and you have no other choice, carefully review both the libraries you’re relying on as well as your own code to ensure you’re not working with code that reads from uninitialized memory, ignores hardware RNG peripheral registers or error conditions, or fails to block when no more entropy is available. Carefully consider the implications for real-time situations where blocking isn’t a viable option. DEVICE MANUFACTURERS / IOT OPERATION SYSTEMS Deprecate and/or disable any direct use of the RNG HAL function in your SDK. Instead, include a CSPRNG API that is seeded using robust and diverse entropy sources with proper hardware RNG handling. The Linux kernel’s implementation of /dev/urandom can serve as an excellent reference. --------------------------------------------------------------- See Dan and Allan discuss their research at DEF CON 29:

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WSOC Charlotte: Local doctor sees spike in patients seeking parasite drug for COVID treatment
by jim bell 13 Aug '21

13 Aug '21

WSOC Charlotte: Local doctor sees spike in patients seeking parasite drug for COVID treatment. https://www.wsoctv.com/news/local/duke-researchers-study-possible-alternate… Ivermectin CHARLOTTE — While there are three COVID-19 vaccines available, doctors and scientists continue researching other medications to fight the coronavirus. They’re focused on helping those who get it early on and to keep them out of the hospital. One medication -- ivermectin -- that is being studied treats parasite infections.Channel 9′s DaShawn Brown found out that a local doctor is swamped with requests for it, even though it hasn’t been approved by the Food and Drug Administration. The majority of the requests are from those who aren’t vaccinated.

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Re: Assange's Case
by professor rat 13 Aug '21

13 Aug '21

In September 1991, Assange was discovered hacking into the Melbourne master terminal of Nortel, a Canadian multinational telecommunications corporation.[32] The Australian Federal Police tapped Assange's phone line (he was using a modem), raided his home at the end of October[45] and eventually charged him in 1994 with 31 counts of hacking and related crimes.[32] In December 1996, he pleaded guilty to 24 charges ..." Wikipedia. The longstanding US allegation against this self-described journalist is that he attempted ( with Bradass ) to break into a US based computer server. US Jurisdiction doesn't appear to be a critical issue for someone who has previously admitted breaking and entering computers in the US and where a prima facie case may exist. Such as the Bradass case. Moving on the statute of limitations - the Mange ran out the clock on allegations of rape and sexual-assault. And it may well be the clock has run out on the Bradass affair. However... There are further allegations re CIA leaks ' Vault Seven ' material. The fact Camp Wikileaks are being so dodgy about this makes their self-described journalist Fuhrer-figure looks guilty...again. To sum up - a case against Assmange has been made that all cypherpunks that don't want journalists rummaging through their computers might support. As for cypherpunks that don't know Assmange is a totally discredited fascist propagandist by now. Well they must be too stupid to be activists, let alone anarchists.

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Bad week for the Gramps Goon Squad
by professor rat 12 Aug '21

12 Aug '21

https://www.palmerreport.com/analysis/donald-trump-and-his-goons-are-having… Yesterday the news broke that the Scottish courts approved a money laundering probe into Donald Trump’s golf properties. The news also broke that federal prosecutors have reportedly decided to criminally indict Matt Gaetz, and are pressuring him to flip on others. Then last night the courts ruled that Dominion’s civil suit against Rudy Giuliani, Sidney Powell, and Mike Lindell could move ahead.

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My life on the left - 1971
by professor rat 12 Aug '21

12 Aug '21

By 1971 I already had experience as an anti-Vietnam-war veteran. In 1967 I took an issue of RAMPARTS magazine for show-and-tell at my Ithaca NY school. Almost everyone was shocked by the sight of children with their faces melted by napalm. One skinhead patriot spat in my face later on. Back in au I went to the big Moratorium march in Melb. I can humblebrag that I did some activism in every one of the last seven decades if you include this one - the Twenties. 1971 and I was opposing Apartheid in the streets and on the Rugby field at Melb. Very exciting for a 16 yo! Soon after this I started looking for books on anarchism. I still have this HIGH TIMES issue with an anarchist article in it. https://www.ebay.com/itm/184890222140?hash=item2b0c50e63c:g:TkwAAOSwBSVgySYi

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Praising Keynes for shits and giggles
by professor rat 12 Aug '21

12 Aug '21

After a couple of decades online I've noticed praising Keynes is a great way to troll both BROWN and RED fascists. And there's a lot to praise - guys like Orwell, Keynes and etc are obviously not anarchists - but then again, anarchists don't have a monopoly on wisdom. And it makes us look better when we recognize that fact.

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Politics govtheory was: assange
by Karl 12 Aug '21

12 Aug '21

Hi jim, You've probably blocked me by now, but On Wed, Aug 11, 2021, 6:56 PM jim bell <jdb10987(a)yahoo.com> wrote: > > The problem, briefly stated, is "How do you defend a country based on > anarchistic or libertarian principles, if they cannot tax themselves to put > on a defense?" > The money and labor rise from people who value defense. This value is clear when the danger is clear. AP is a little similar to a culture I heard of among indigenous people in canada. There is a nation of them who do not provide for outsiders to trespass on their land. The punishment for trespass is death, and that's just a part of their shared culture and has been for as long as anybody knows, so the entire nation would be familiar with supporting it. When living off the land, if the ecosystem is mistreated (e.g. overhunted by a neighbor), your families die, so managing the impact of others has been important. But jim and I disagree on the result of money. I think I see supporting unlimited wealth as oppressive and jim sees it as freeing, not sure. Regardless you probably need some kind of financial government to provide for unlimited wealth, since people as a whole only have so much demand. Most people don't want advertisements in their search results, and those ads produce a lot of unnatural demand. >

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Cryptocurrency: Great Keynesian Coup Of August 1971: Fifty Years Later
by grarpamp 12 Aug '21

12 Aug '21

The Great Keynesian Coup Of August 1971: Fifty Years Later https://mises.org/wire/great-keynesian-coup-august-1971-fifty-years-later by William Anderson via The Mises Institute On August 15, 1971, the last remains of what had been a magnificent monetary system died a terrible death, and the American academic, political, business, and media elites led the cheers. The Dow Jones Average jumped by more than 32 points the next day. A de facto national default was spun as a great liberation from a tyrannical financial arrangement that had plagued humanity for generations. A half century later the disinformation continues, as intellectual bankruptcy parallels the financial bankruptcy of that event. I write, of course, of the decision by President Richard Nixon to officially close the “gold window,” through which the US government was obligated to sell its gold stores to foreign governments at $35 an ounce, which even then was a bargain. As Nixon’s regime encouraged the Federal Reserve System to inflate the dollar to pay for its bloated military and welfare spending, as had the Johnson and Kennedy regimes before him, it became apparent that the US dollar was quickly losing value. The United States was in rapid decline—and the dollar was falling with the nation’s prestige. What happened? There are several accounts, and I will give the main ones, ending with the Austrian perspective. The first will be the Keynesian, the second the monetarist (Chicago school), the third the supply-side version, and the fourth from the Austrians. Before doing that, however, I will give a brief account of the events that began with the Bretton Woods Conference in 1944 and ended in national disgrace, an ignominy that even now the official American narrative refuses to recognize. The Bretton Woods Conference didn’t occur in a vacuum. Just a month before, Allied troops had secured a beachhead in France and had begun to slowly push the German army eastward. Across the European continent, armies from the Soviet Union were slowly destroying the Axis forces from the other direction. In the Pacific, US bombers were beginning to lay waste to Japanese cities, and the Japanese armies were suffering defeat after defeat. Final victory for the USA and its allies would not come for another thirteen months, but even in July 1944, it was clear how the war would end. The US State Department explains the stated purpose of the conference: to help reestablish trading relations in the postwar world: The lessons taken by U.S. policymakers from the interwar period informed the institutions created at the conference. Officials such as President Franklin D. Roosevelt and Secretary of State Cordell Hull were adherents of the Wilsonian belief that free trade not only promoted international prosperity, but also international peace. The experience of the 1930s certainly suggested as much. The policies adopted by governments to combat the Great Depression—high tariff barriers, competitive currency devaluations, discriminatory trading blocs—had contributed to creating an unstable international environment without improving the economic situation. This experience led international leaders to conclude that economic cooperation was the only way to achieve both peace and prosperity, at home and abroad. Some cynicism can be excused if one sees a disconnect between the high-minded rhetoric of the document and the actual policies of the Wilson and Roosevelt administrations that played a major role in creating the calamities from 1917 to the end of World War II. But then, it is a rare occurrence when government bombast and the truth intersect. Not surprisingly, Bretton Woods was an attempt by governments to deal with the previous disastrous results of intervention by imposing even more intervention. In his classic What Has Government Done to Our Money, Murray N. Rothbard (who will figure heavily in my interpretation of the August 15 events) describes the Bretton Woods Agreement: While the Bretton Woods system worked far better than the disaster of the 1930s, it worked only as another inflationary recrudescence of the gold-exchange standard of the 1920s and—like the 1920s—the system lived only on borrowed time. The new system was essentially the gold-exchange standard of the 1920s but with the dollar rudely displacing the British pound as one of the “key currencies.” Now the dollar, valued at 1/35 of a gold ounce, was to be the only key currency. The other difference from the 1920s was that the dollar was no longer redeemable in gold to American citizens; instead, the 1930’s system was continued, with the dollar redeemable in gold only to foreign governments and their Central Banks. No private individuals, only governments, were to be allowed the privilege of redeeming dollars in the world gold currency. In the Bretton Woods system, the United States pyramided dollars (in paper money and in bank deposits) on top of gold, in which dollars could be redeemed by foreign governments; while all other governments held dollars as their basic reserve and pyramided their currency on top of dollars. (p. 99) To put it another way, the Bretton Woods Agreement really was a scheme to give the appearance of “sound money” all the while ensuring that the sound money regime that existed prior to the outbreak of World War I would not be reinstituted. Furthermore, Henry Hazlitt, who then was writing editorials for the New York Times (how the mighty have fallen!), saw through everything and predicted that the new monetary arrangements would lead to disastrous consequences. He wrote: The greatest single contribution the United States could make to world currency stability after the war is to announce its determination to stabilize its own currency. It will incidentally help us, of course, if other nations as well return to the gold standard. They will do it, however, only to the extent that they recognize that they are doing it not primarily as a favor to us but to themselves. But Hazlitt knew that governments in 1944 were institutionally incapable of returning to sound money and that the elites in government, academe, and the media were hostile to anything but fiat money. Ultimately, Hazlitt and the NYT would part ways over his disagreements with the Keynesian economic views of the era. The NYT would continue to endorse monetary socialism and today features Paul Krugman, who has all but endorsed the money printing of modern monetary theory. In other words, Hazlitt predicted the demise of the Bretton Woods accord twenty-seven years before it officially collapsed. As previously noted, the US dollar was set as the world’s “reserve” currency and it was set at $35 per ounce of gold, which meant that foreign governments and central banks could purchase US gold at that price if they wished to redeem their dollars on something other than dollar-denominated goods and assets. Rothbard points out that because the agreements set the currency exchange values at prewar levels, the dollar was undervalued and European currencies overvalued, thus increasing the demand for dollars. (For reasons of length, I do not cover the Marshall Plan and how international monetary policies fit into trying to make it work. Suffice it to say the Marshall Plan has been given far too much credit for Europe’s postwar recovery. In many instances, it actually impeded recovery and it was only after the governments of Western European nations eased the economic controls set during Nazi occupations that Europe had a true economic recovery.) The purposeful devaluing of the US dollar provided incentives for the Federal Reserve System to inflate the dollar, which it did in the postwar years and beyond (and is doing with a vengeance today). Because the law forbade Americans from buying and owning gold (with some exceptions for jewelry and official coin collections), the US government did not have to worry about its inflationary policies creating a domestic run on its gold reserves. That would not be the case overseas, however. American economists and politicians embraced Keynesian theories that emphasized expansive government programs financed through deficit spending. The few dissenters such as economists Ludwig von Mises and F.A. Hayek were dismissed as “mossbacks” and “reactionaries,” as the American media, academic, and political establishments saw the New Economics as a gateway to easy prosperity. European governments, and especially the French government led by Charles de Gaulle (who was advised by the classical gold-standard economist Jacques Rueff), by the 1960s began to purchase US gold in earnest. In the early postwar years, it made sense to hold officially undervalued dollars, but in less than two decades, the dollar had become hopelessly overvalued relative to most European currencies. Lyndon Johnson’s Vietnam war and his Great Society welfare programs had to be financed, and the government chose inflation. Buying US gold at what was a bargain price was a way that foreign governments could do an end run around a monetary exchange system that was becoming increasingly unbalanced. In 1968, the US government tried to put together a stopgap measure to stop the gold hemorrhage. (Rothbard goes into the details of the measures, noting that they were doomed to fail because they were based upon faulty economic analysis.) By trying to sever the link between the US dollar and gold sold on the free market, the Johnson administration claimed that the new measures would force down the price of gold to less than $35 an ounce, making US stores an unattractive buy. As any competent Austrian economist would predict, however, the runs on US gold did not diminish but rather intensified, and by the summer of 1971, the US economy was stagnant, prices were rising, and President Nixon on August 15 announced his “Phase One” economic plan of price controls and temporarily closing the gold window. Again, any competent economist would know that this move would end in failure, but the move initially was popular in the media and with the public. Gene Healy writes: There was no national emergency in the summer of ’71: unemployment stood at 6 percent…. Yet, after Nixon’s announcement, the markets rallied, the press swooned, and, even though his speech pre‐empted the popular Western Bonanza, the people loved it, too—75 percent backed the plan in polls. On the monetary side, the next step was the implementation in December of the Smithsonian Agreement, which raised the official price of US government gold to $38 an ounce and allowed some flexibility in the fixed exchange rates, but in the end, the combination of US inflation and economic stagnation on the home front would lead to the total collapse of fixed rates. By 1973, the dollar was hopelessly overvalued and ultimately the present system of floating exchange rates prevailed. Keynesian Policies One of the most famous statements to come from this episode of “Nixon Shock” was the president’s statement to his advisers, “We are all Keynesians now.” It also was the most accurate statement anyone in the government would make. In one action, Nixon cut ties to gold, what J.M. Keynes had called “that barbarous relic.” The devaluation of the dollar would help exports, and Nixon saw government intervention as necessary to “balance power” between labor unions and corporations. In fact, his Federal Reserve chairman, Arthur Burns, already had announced his fealty to Keynesian economics, and Nixon himself had surrendered any previous notions of free markets to Keynesian-inspired policies. The PBS Commanding Heights series reported: [W]hatever the effects of the Vietnam War on the national consensus in the 1960s, confidence had risen in the ability of government to manage the economy and to reach out to solve big social problems through such programs as the War on Poverty. Nixon shared in these beliefs, at least in part. “Now I am a Keynesian,” he declared in January 1971—leaving his aides to draft replies to the angry letters that flowed into the White House from conservative supporters. He introduced a Keynesian “full employment” budget, which provided for deficit spending to reduce unemployment. A Republican congressman from Illinois told Nixon that he would reluctantly support the president's budget, “but I'm going to have to burn up a lot of old speeches denouncing deficit spending.” To this Nixon replied, “I'm in the same boat.” Whatever fiscal discipline Nixon had promised during his political campaign was out the window. Even if his enemies in the academic and political worlds (and they were legion) would always hate him, nonetheless he was giving them what they always had wanted: government control of the economy. Not surprisingly, while his policies were politically popular at the beginning, the 1970s ultimately became known for stagflation (simultaneous increases in unemployment and inflation—something Keynesians claimed was impossible), gasoline and natural gas shortages (due to price controls), and a general feeling of despair. Democrats ultimately would drive Nixon from office three years later, but they endorsed his economic policies, and especially his penchant for price controls. President Jimmy Carter would push his wage-price “guidelines” in an unsuccessful attempt to bring down double-digit inflation, and when Senator Ted Kennedy ran for the Democratic nomination in 1980, he made price controls the centerpiece of his economic policies. Ironically, Carter and the Democrats did embark on a supply-side venture of their own, deregulating the financial and transportation sectors and laying the groundwork to deregulate telecommunications. Thus, the party of the New Deal actually undid part of the legacy of Franklin Roosevelt—and actually provided a long-run boost to the economy, all the while being ignorant of their accomplishments. Supply-Siders While the group of economists that called themselves supply-siders raised important issues about how government intervention into the economy was causing stagflation and other economic ills, nonetheless their statements on Nixon’s actions were shortsighted. During the 1980 presidential campaign in which Ronald Reagan cast his lot with supply-side economics, Jack Kemp, who championed the supply-side policies in Congress, declared that Nixon’s error had been to go to floating exchange rates instead of holding to the fixed rates of the Bretton Woods accord. Nixon’s actions, as dishonest as they were, did not occur in a vacuum. Holding to fixed exchanged rates and a (very) modified gold standard would have required the kind of fiscal and monetary discipline that had not existed in Washington since the Great Depression and certainly was not going to begin in August 1971. We should be clear: Nixon did not unilaterally destroy a productive arrangement. Nixon’s actions unwittingly exposed the bankruptcy of US government policies even though he would spin it as the US fending off an unjustified foreign attack on the dollar and on US gold supplies. During the era of the international gold standard that fell apart in 1914, currency rates were fixed, but not against each other but rather to a measure of gold. Any attempts to game the system—as the US government did on a regular basis in the postwar years—would have quickly been detected, with gold outflows ultimately helping to counter cheating. Although the Bretton Woods accord was created to emulate the old gold standard with its fixed rates, it ultimately failed because governments are destructive. By summer’s end of 1914, the governments of Europe had gone to war and destroyed an international gold standard that took decades to build. In 1971, governments armed with Keynesian dogma laid waste to an economic system almost as surely as the Guns of August brought Western civilization to its knees. Monetarists When Nixon announced the imposition of wage and price controls, Milton Friedman of the University of Chicago loudly denounced them as an “utter failure.” However, as Rothbard wrote, Friedman was not unhappy to see the last ties of the dollar to gold broken. As an outspoken advocate of floating fiat exchange rates, Friedman for years had denounced gold ties to the dollar, as Rothbard explains: Since the United States went completely off gold in August 1971 and established the Friedmanite fluctuating fiat system in March 1973, the United States and the world have suffered the most intense and most sustained bout of peacetime inflation in the history of the world. It should be clear by now that this is scarcely a coincidence. Before the dollar was cut loose from gold, Keynesians and Friedmanites, each in their own way devoted to fiat paper money, confidently predicted that when fiat money was established, the market price of gold would fall promptly to its nonmonetary level, then estimated at about $8 an ounce. In their scorn of gold, both groups maintained that it was the mighty dollar that was propping up the price of gold, and not vice versa. Since 1971, the market price of gold has never been below the old fixed price of $35 an ounce, and has almost always been enormously higher. (pp. 109–10) In Friedman’s defense, the floating exchange rates didn’t cause the inflation of the 1970s. However, those floating rates imposed no financial discipline on the US government, and when things went south presidential administrations blamed foreign governments. When the dollar fell against European currencies in 1978, President Carter signed off on a scheme in which the Federal Reserve System underwrote a massive purchase of dollars in order to prop up the currency. Not surprisingly, the arrangement failed to strengthen the dollar over time. Austrians While Keynesians and monetarists might look down on gold as money (or any monetary ties to gold), Austrians are not afraid to face the ridicule from elites. More than anyone else, however, Austrians such as Rothbard understood completely what was happening in 1971, and they were not fooled by the government’s various monetary tricks as were others. Rothbard writes: All pro-paper economists, from Keynesians to Friedmanites, were now confident that gold would disappear from the international monetary system; cut off from its “support” by the dollar, these economists all confidently predicted, the free-market gold price would soon fall below $35 an ounce, and even down to the estimated “industrial” nonmonetary gold price of $10 an ounce. Instead, the free price of gold, never below $35, had been steadily above $35, and by early 1973 had climbed to around $125 an ounce, a figure that no pro-paper economist would have thought possible as recently as a year earlier. Far from establishing a permanent new monetary system, the two-tier gold market only bought a few years of time; American inflation and deficits continued. Eurodollars accumulated rapidly, gold continued to flow outward, and the higher free-market price of gold simply revealed the accelerated loss of world confidence in the dollar. (pp. 104–05) The American economy and the dollar rebounded during the 1980s in part because of lower tax rates and in part because of the deregulatory efforts instituted by the Carter administration. Unfortunately, the favorable economic conditions did not lead to fiscal soundness, but, instead, seemed to encourage even more reckless behavior in Washington. For the last twenty-two years, the economy has seen one financial bubble after another: first the tech bubble of the late 1990s, then the housing bubble that burst in 2008, and now a combination of housing and equities seems to be rising well out of synch with market fundamentals. As they did in 1971, the elite economists of our day are the cheerleaders for fiscal foolishness. Lest one believe I am exaggerating, this is from a recent column by Paul Krugman in the New York Times, which lost its way editorially after the editorial leadership pushed out Henry Hazlitt. Endorsing the so-called Infrastructure Bill, Krugman writes: Imagine, to use a round number, that the federal government were to go out right now and borrow $1 trillion—and that it were to do so without making any provisions for servicing the additional debt. That is, it wouldn’t raise any taxes or cut any spending to pay off the principal; it wouldn’t even do anything to cover interest payments, simply borrowing more money as interest came due. Under these circumstances the debt would grow over time. But it wouldn’t grow very fast: The current interest rate on long-term U.S. debt is less than 1.2 percent, so after a decade the debt would have risen only about 13 percent. And debt growth would be vastly outpaced by growth in the economy: The Congressional Budget Office projects a 50 percent rise in dollar G.D.P. over the next 10 years. Debt wouldn’t snowball; relative to the economy, it would melt. So the fact that the infrastructure bill would, in practice, pay for public investment with borrowed money isn’t anything to worry about. If the investment is worth undertaking—and it is—we should just do it. One can imagine that Krugman would have championed Nixon’s moves, from abrogating the Bretton Woods Agreement to imposing wage and price controls. To a Keynesian like Krugman and those that came before him, the economy works best when governments spend recklessly with no constraints. Austrians know better. The collapse of the monetary order in 1971 reflected the massive dislocations and malinvestment of resources that ultimately turned the decade into one crisis after another, and the current economy is facing risks of even greater magnitude. Unfortunately, Keynesians rule the day, just as they did fifty years ago. As Charles-Maurice de Talleyrand wrote of the Bourbons in the years after the French Revolution, “They learned nothing, and they forgot nothing.” One can say the same for the Keynesians. A half century after The Crisis, Keynesians seem hellbent on creating new crises and printing money to “fix” them. http://triplecrisis.com/a-first-default-closing-the-gold-window/ https://mises.org/wire/today-1971-president-nixon-closes-gold-window https://2001-2009.state.gov/r/pa/ho/time/wwii/98681.htm https://mises.org/library/what-has-government-done-our-money https://mises.org/wire/why-hazlitt-opposed-bretton-woods-system https://reason.com/1986/04/01/the-great-twentieth-century-fo/ https://www.cato.org/commentary/remembering-nixons-wage-price-controls https://en.wikipedia.org/wiki/Nixon_shock https://www.pbs.org/wgbh/commandingheights/shared/minitext/ess_nixongold.ht… https://www.investopedia.com/terms/s/supply-sidetheory.asp https://www.washingtonpost.com/archive/politics/1978/11/02/carter-moves-to-… https://www.nytimes.com/2021/08/05/opinion/infrastructure-bill-financing.ht… https://www.cnbc.com/quotes/US10Y https://www.cbo.gov/publication/57339 https://www.nytimes.com/2019/01/09/opinion/melting-snowballs-and-the-winter…

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Dream-girl for that Gramps Nutcase
by professor rat 12 Aug '21

12 Aug '21

bradheath ·8h A federal judge has rejected ex-Trump lawyer Sidney Powell's argument that "no reasonable person" would believe her election-fraud claims were statements of fact. Dominion's suits against her, Giuliani and MyPillow will go forward. https://storage.courtlistener.com/recap/gov.uscourts.dcd.227759/gov.uscourt…

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