Entries Tagged "random numbers"
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Kaspersky has a detailed blog post about a new piece of sophisticated malware that it’s calling Reductor. The malware is able to compromise TLS traffic by infecting the computer with hacked TLS engine substituted on the fly, “marking” infected TLS handshakes by compromising the underlining random-number generator, and adding new digital certificates. The result is that the attacker can identify, intercept, and decrypt TLS traffic from the infected computer.
The Kaspersky Attribution Engine shows strong code similarities between this family and the COMPfun Trojan. Moreover, further research showed that the original COMpfun Trojan most probably is used as a downloader in one of the distribution schemes. Based on these similarities, we’re quite sure the new malware was developed by the COMPfun authors.
The COMpfun malware was initially documented by G-DATA in 2014. Although G-DATA didn’t identify which actor was using this malware, Kaspersky tentatively linked it to the Turla APT, based on the victimology. Our telemetry indicates that the current campaign using Reductor started at the end of April 2019 and remained active at the time of writing (August 2019). We identified targets in Russia and Belarus.
Turla has in the past shown many innovative ways to accomplish its goals, such as using hijacked satellite infrastructure. This time, if we’re right that Turla is the actor behind this new wave of attacks, then with Reductor it has implemented a very interesting way to mark a host’s encrypted TLS traffic by patching the browser without parsing network packets. The victimology for this new campaign aligns with previous Turla interests.
We didn’t observe any MitM functionality in the analyzed malware samples. However, Reductor is able to install digital certificates and mark the targets’ TLS traffic. It uses infected installers for initial infection through HTTP downloads from warez websites. The fact the original files on these sites are not infected also points to evidence of subsequent traffic manipulation.
Wow, is this an embarrassing bug:
Yubico is recalling a line of security keys used by the U.S. government due to a firmware flaw. The company issued a security advisory today that warned of an issue in YubiKey FIPS Series devices with firmware versions 4.4.2 and 4.4.4 that reduced the randomness of the cryptographic keys it generates. The security keys are used by thousands of federal employees on a daily basis, letting them securely log-on to their devices by issuing one-time passwords.
The problem in question occurs after the security key powers up. According to Yubico, a bug keeps “some predictable content” inside the device’s data buffer that could impact the randomness of the keys generated. Security keys with ECDSA signatures are in particular danger. A total of 80 of the 256 bits generated by the key remain static, meaning an attacker who gains access to several signatures could recreate the private key.
Boing Boing post.
EDITED TO ADD (6/12): From Microsoft TechNet Security Guidance blog (in 2014): “Why We’re Not Recommending ‘FIPS Mode’ Anymore.“
Turns out that the software a bunch of CAs used to generate public-key certificates was flawed: they created random serial numbers with only 63 bits instead of the required 64. That may not seem like a big deal to the layman, but that one bit change means that the serial numbers only have half the required entropy. This really isn’t a security problem; the serial numbers are to protect against attacks that involve weak hash functions, and we don’t allow those weak hash functions anymore. Still, it’s a good thing that the CAs are reissuing the certificates. The point of a standard is that it’s to be followed.
Matthew Green wrote a fascinating blog post about the NSA’s efforts to increase the amount of random data exposed in the TLS protocol, and how it interacts with the NSA’s backdoor into the DUAL_EC_PRNG random number generator to weaken TLS.
New research: “Verified Correctness and Security of mbedTLS HMAC-DRBG,” by Katherine Q. Ye, Matthew Green, Naphat Sanguansin, Lennart Beringer, Adam Petcher, and Andrew W. Appel.
Abstract: We have formalized the functional specification of HMAC-DRBG (NIST 800-90A), and we have proved its cryptographic security — that its output is pseudorandom — using a hybrid game-based proof. We have also proved that the mbedTLS implementation (C program) correctly implements this functional specification. That proof composes with an existing C compiler correctness proof to guarantee, end-to-end, that the machine language program gives strong pseudorandomness. All proofs (hybrid games, C program verification, compiler, and their composition) are machine-checked in the Coq proof assistant. Our proofs are modular: the hybrid game proof holds on any implementation of HMAC-DRBG that satisfies our functional specification. Therefore, our functional specification can serve as a high-assurance reference.
Eddie Tipton, a programmer for the Multi-State Lottery Association, secretly installed software that allowed him to predict jackpots.
What’s surprising to me is how many lotteries don’t use real random number generators. What happened to picking golf balls out of wind-blown steel cages on television?
The venture is built on Alex’s talent for reverse engineering the algorithms — known as pseudorandom number generators, or PRNGs — that govern how slot machine games behave. Armed with this knowledge, he can predict when certain games are likeliest to spit out moneyinsight that he shares with a legion of field agents who do the organization’s grunt work.
These agents roam casinos from Poland to Macau to Peru in search of slots whose PRNGs have been deciphered by Alex. They use phones to record video of a vulnerable machine in action, then transmit the footage to an office in St. Petersburg. There, Alex and his assistants analyze the video to determine when the games’ odds will briefly tilt against the house. They then send timing data to a custom app on an agent’s phone; this data causes the phones to vibrate a split second before the agent should press the “Spin” button. By using these cues to beat slots in multiple casinos, a four-person team can earn more than $250,000 a week.
It’s an interesting article; I have no idea how much of it is true.
The sad part is that the slot-machine vulnerability is so easy to fix. Although the article says that “writing such algorithms requires tremendous mathematical skill,” it’s really only true that designing the algorithms requires that skill. Using any secure encryption algorithm or hash function as a PRNG is trivially easy. And there’s no reason why the system can’t be designed with a real RNG. There is some randomness in the system somewhere, and it can be added into the mix as well. The programmers can use a well-designed algorithm, like my own Fortuna, but even something less well-thought-out is likely to foil this attack.
Wired is reporting on a new slot machine hack. A Russian group has reverse-engineered a particular brand of slot machine — from Austrian company Novomatic — and can simulate and predict the pseudo-random number generator.
The cell phones from Pechanga, combined with intelligence from investigations in Missouri and Europe, revealed key details. According to Willy Allison, a Las Vegas-based casino security consultant who has been tracking the Russian scam for years, the operatives use their phones to record about two dozen spins on a game they aim to cheat. They upload that footage to a technical staff in St. Petersburg, who analyze the video and calculate the machine’s pattern based on what they know about the model’s pseudorandom number generator. Finally, the St. Petersburg team transmits a list of timing markers to a custom app on the operative’s phone; those markers cause the handset to vibrate roughly 0.25 seconds before the operative should press the spin button.
“The normal reaction time for a human is about a quarter of a second, which is why they do that,” says Allison, who is also the founder of the annual World Game Protection Conference. The timed spins are not always successful, but they result in far more payouts than a machine normally awards: Individual scammers typically win more than $10,000 per day. (Allison notes that those operatives try to keep their winnings on each machine to less than $1,000, to avoid arousing suspicion.) A four-person team working multiple casinos can earn upwards of $250,000 in a single week.
The easy solution is to use a random-number generator that accepts local entropy, like Fortuna. But there’s probably no way to easily reprogram those old machines.
Sidebar photo of Bruce Schneier by Joe MacInnis.