On 2026-11-06, Google DeepMind (@GoogleDeepMind) and VP Science Pushmeet Kohli published research: under human supervision, AI agents found two weaknesses in legacy 1024-bit RSA—signature padding adds no extra protection once an attacker controls about half the signed block (sandbox replay ~3.5× less CPU than prior), and a batch-factoring algorithm cuts average cost per additional same-size key by about 30×. Official caveat: modern 2048-bit and larger protocols remain unaffected.

Key Takeaways

  • ✓Source: @GoogleDeepMind post on 2026-11-06 + Pushmeet Kohli X Article; two technical PDFs (signatures / Batch NFS)
  • ✓Scope: legacy 1024-bit RSA only; official statement that 2048-bit and larger remain secure
  • ✓Signatures: once an attacker controls ~half the signed block, padding adds no protection; sandbox on a known 1024-bit benchmark key used ~3.5× less CPU and under 1/1000 of full break cost
  • ✓Short fingerprints (e.g. 32-byte): theoretical estimate ~1600× better than prior best for 1024-bit keys
  • ✓Batch factoring: for many same-size keys, average cost per additional key ~30× lower vs prior batch methods
Google DeepMind: Human-Guided AI Agents Speed Cryptanalysis; Two Weaknesses in Legacy 1024-bit RSA; 2048-bit+ Remains Safe
🖼️Official Media
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In-Depth Technical Analysis

Core Background & Industry Pain Points

Modern encryption rests on computational hardness: multiplying large primes is easy; factoring the product is not. Cryptographers have long used retired RSA-1024 as a safe proving ground, but major advances historically took years. On 2026-11-06, Google DeepMind reported that human-supervised AI agents can probe these hardness assumptions faster, lowering the computational budget needed against legacy 1024-bit systems—while stating that widely deployed 2048-bit and larger protocols remain unaffected.

Architecture Highlights & Internals

The work is led by Dj Dvijotham and Abhradeep Thakurta, with Nadia Heninger (UC San Diego / Inria) and Emmanuel Thomé (Inria). One line targets signature padding: if an attacker can feed chosen inputs to a signing device and control roughly half the signed block, padding adds no protection and forgery collapses to the no-padding case. The second line targets batch factoring of many same-size moduli: agents found an algorithm with better asymptotic complexity, cutting the incremental cost after a large shared precomputation. All experiments were sandboxed; no live systems were touched.

Authoritative Benchmarks & Measured Scores

Figures below are DeepMind / collaborator-reported, not independently reproduced here. In sandbox replay on an already-solved 1024-bit academic benchmark key, the agent-engineered implementation used about 3.5× less CPU than prior work and under one-thousandth the compute of a full key break. For short fingerprints (e.g. 32 bytes), theoretical estimates put a new algorithm about 1600× better than the previous best at 1024 bits. For batch factoring many same-size keys, average cost per additional 1024-bit key is about 30× lower than prior batch methods.

Developer Hands-on Guide

Read Pushmeet Kohli's X Article and the two GCS technical PDFs (Faster Affine Root for signatures; Fan Factories / Batch NFS for factoring). Inventory any remaining 1024-bit RSA certs, HSMs, or blind-signing oracles; migrate production to 2048+ and plan post-quantum paths. When building agent security tooling, include controlled signing oracles and padding fraction in the threat model—without overstating today's 2048-bit risk.

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