Typo-squatted domain + MitM proxy nets four PyPI accounts, injects malware into 30M-download package

OpenSSF

Attackers registered a one-character lookalike of pypi.org, ran a MitM proxy to capture TOTP sessions and mint API tokens, then published a Scavenger Loader variant via num-to-words—a transitive dependency of Hugging Face Transformers. WebAuthn would have blocked the attack; response took 40 volunteer hours across registrars and maintainers.

Self-play bug injection loop trains coding agents without human data, beats static datasets

aiware

The framework chains three components: SEER, an RL model trained on real GitHub issues; SelfPlay-IO, where a bug-injector and bug-fixer agent compete to generate synthetic training data; and LiveAgent, which freezes weights but lets agents author new tools on-the-fly. Benchmarks show SelfPlay-IO outperforms static real-world datasets.

ACM: RL infrastructure must validate system optimizations against learning semantics, not just GPU utilization

ACM

VRL's evolution from research to production reveals that optimizations like speculative decoding, resharding, and batching changes silently alter training dynamics—policy consistency, reward matching, convergence. The talk introduces trajectory-level asynchrony (Lumina) and argues for principled risk classification of optimizations rather than empirical validation alone.

CppCon: C++ performance folklore fails under empirical testing

CppCon

Jonathan Stein walks through concrete cases where accepted C++ wisdom breaks down: inline template advice that increases register pressure, flawed CPU capacity math, architecture benchmarks run on wrong workloads, and pointer-to-member-function overhead. Compiler bugs compound the problem — the fix is measurement, not intuition.

NCSC chief warns AI commoditizes premium vulns, threatens offensive talent pipelines

OffensiveCon

Ollie Whitehouse argues defense requires a functioning offensive ecosystem, then details how LLMs are eroding the premium vulnerability market and gutting entry-level researcher incentives. He outlines the NCSC's Pammal bifurcation strategy—supporting responsible vendors while easing disruption of irresponsible ones—and calls for evidence-based metrics on defensive ROI.

DeepMind's AlphaEvolve improves TSP hardness ratio and Ramsey bounds unsolved for decades

Simons Institute for the Theory of Computing

AlphaEvolve mutates programs that generate candidate proof objects—gadgets and graphs—scored by fast heuristic verifiers, then exhaustively verified. It tightened TSP inapproximability to 111/110, matched analytical max-cut bounds, and pushed Ramsey lower bounds 1-4 nodes past prior state-of-the-art where SAT/SMT solvers stalled.