LLM Agents

3 posts

2026-07-024 minSentinelOnelow
Context Engineering | Compaction & Agent Memory for Automated Malware Analysis
SentinelLABS evaluated OpenAI's native compaction feature in the Responses API for automated binary analysis workflows. Compaction reduced input tokens by approximately 86% with no aggregate score degradation, but domain object modeling quality decreased, indicating that structural reasoning can be flattened during context compression. The research advocates for a context-engineering strategy that separates compacted working memory from durable artifact storage and treats compaction as lossy until validated.
2026-05-135 minSophosmedium
We let OpenClaw loose on an internal network. Here’s what it found
Sophos researchers successfully deployed the OpenClaw AI agent in a controlled red team engagement against a legacy on-prem network. By implementing strict safety guardrails and custom-built skills, the agent autonomously conducted Active Directory reconnaissance and exploitation, significantly reducing operational time while identifying 23 actionable security findings.
2026-05-133 minTrail of Bitslow
How we made Trail of Bits AI-native (so far)
Trail of Bits details their organizational shift to an AI-native workflow using Claude Code and autonomous agents. The post outlines their strategy for overcoming employee resistance, establishing an AI Maturity Matrix, and securing agent autonomy through sandboxing, curated marketplaces, and strict usage policies.