From Attack Surface to Defense Architecture: Compositional Security for Agentic Coding Harnesses
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AI coding harnesses couple language models to shells, filesystems, and network sockets, turning the harness into an automated Living-off-the-Land (LotL) platform: once an adversary injects instructions into retrieved content, dual-use binaries such as bash, curl, and find become the payload. We argue that security in agentic systems is a structural property of the cognitive architecture and permission composition rather than an emergent property of individual models. Static regex blacklists miss structural evasions, whereas LLM-as-a-Judge guardrails incur high latency while over-blocking benign work. We present ActiveSecHarness, a neurosymbolic reference-monitor architecture built around Separation of Intelligence and Authority. It combines (1) Macaroon-inspired HMAC capability tokens across four Trust and Authority Rings, (2) a 2D product taint lattice {L} = {L}_{trust} {L}_{sens} and a workspace provenance ledger that prevents secret laundering across disk, (3) deterministic Ring-0 OS/tool guards, and (4) bytecode certificates, split-horizon audit logs, self-healing security test synthesis, and an adaptive UserWikiManager. Across N=252 fixtures (120 attack, 120 benign, 12 kill chains), a live local LLM judge (qwen3:4b) refuses 98.3\% of benign work at 142.3\,ms latency, whereas Ring 0 achieves ABR=1.000 and FPR=0.000 in 12.7\,μs (11{,}200faster). In a multi-step trajectory ablation, an oracle Conseca-style stateless policy misses 4/12 kill chains (ABR=0.667) and coarse Boolean taint blocks 83.3\% of benign workflows, while our 2D product lattice achieves ABR=1.000 and FPR=0.000 at 20\,μs per step.
Autores
Simon Hegelich, Bardh Prenkaj, Habiba Sarhan, Morteza Shahrezaye, Kolja Hegelich, Christian Montag, Ralf Schneider, Erik Cambria
Categorias
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