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Attack on Old ANSI Random Number Generator

Almost 20 years ago, I wrote a paper that pointed to a potential flaw in the ANSI X9.17 RNG standard. Now, new research has found that the flaw exists in some implementations of the RNG standard.

Here’s the research paper, the website — complete with cute logo — for the attack, and Matthew Green’s excellent blog post on the research.

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Proof that HMAC-DRBG has No Back Doors

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.

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Hacking Slot Machines by Reverse-Engineering the Random Number Generators

Interesting story:

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 money¬≠insight 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 of 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.

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Predicting a Slot Machine's PRNG

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.

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