AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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1,407 papers
The proposed HammingMark is a semantic watermarking method that uses the semantic hash of the preceding sentence as a dynamic center and accepts candidates whose hashes fall within its Hamming neighborhood, which achieves strong robustness, high detectability, and near-unwatermarked generation quality.
This work introduces ToolFence, which compiles a typed authorization blueprint before execution, enforces it through a deterministic monitor, and when the blueprint is incomplete asks a judge to grant new capabilities rather than adjudicate each concrete call, improving runtime efficiency.
OPFL calibrates an empirical boundary offline and uses it to distinguish benign numerical deviations from malicious manipulation, and adopts optimistic verification by post auditing only sampled training steps to reduce the cost of expensive MPC replay.
These measurements turn correlation from a post-hoc warning into an auditable allocation decision and turn correlation from a post-hoc warning into an auditable allocation decision.
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This work introduces \method{}, a framework for jailbreaking through text-only continuation interfaces that permit repeated sampling and assistant-prefix continuation, and achieves the highest mean score most comparisons against baselines.
Experiments show that SKILLLITE improves malicious Skill detection across different compact LLM backbones and outperforms existing representative auditing baselines, and generalizes to behaviorally confirmed in-the-wild malicious Skills.
This work proposes VaccineBooster, a single alignment procedure that combines embedding perturbation and weight-level gradient attenuation within each training step, and indicates a trade-off: embedding perturbation primarily reduces flagged harmful content, whereas gradient attenuation primarily preserves explicit ref...
These findings show that gradient-based signals can support multi-turn jailbreak detection, but reliable deployment requires calibration on realistic benign conversations, short-window scoring, length-aware thresholds, and evaluation across attack types and model architectures.
CounterSteer largely neutralizes instructional takeover: a black-box framing search cracks 3 of 18 development samples, and Parameter manipulation--attacker-chosen arguments in otherwise legitimate calls--is only partially resisted.
The results suggest that private dense retrieval is already practical for moderately sized, privacy-sensitive corpora when minute-scale latency is acceptable, and formulates a two-round cryptographic protocol that provides both guarantees.
A personal language agent that acts for its owner across private and shared conversations can learn a fact from one audience and later place it in the context it assembles for another. We study authorization before context across the whole memory lifecycle. Each memory item carries the audience present when it was reco...
A key observation is that reference models serve only to reveal how an example behaves under models not trained on it, and that querying the target model on nearby samples yields the same information, and that querying the target model on nearby samples yields the same information.
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Oct 30, 2026
Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.
Gemini 4 Carbon is our strongest model with state-of-the-art cybersecurity and long horizon capabilities.
Gemini 3.8 Flash and 3.8 Flash Cyber deliver next-generation intelligence for agentic workflows and cybersecurity.
Google introduces Gemini 3.5 Flash Cyber, a lightweight cybersecurity model to find and patch vulnerabilities.
Students from the MIT Cybersecurity Clinic help local governments and other vulnerable organizations defend against digital threats.
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