Knowledge Base Regulation Tracker Standards & Frameworks OSS Directory AI Incident Database Research Paper Library Case Studies Society Articles News Jobs About Charter Sign inBecome a Member
Home/Research Paper Library/System-level Defense against Indirect Prompt Injection Attacks

System-level Defense against Indirect Prompt Injection Attacks

An early system-level defence treating the LLM as untrusted and enforcing information-flow policies around it, a precursor to CaMeL and FIDES.

information flowsystem securityagents

Research question

Can a system-level security architecture stop injection regardless of model behaviour?

Key findings

  • f-secure LLM system separates planning from execution and tracks trust labels - Blocks all tested injection attacks at the system level

Sources

PreviousSecAlignNextEIA

Contribute

Spot an error, or know a record we should add? Members can propose additions and submit corrections.

Submit researchReport a correction or request removal

Related in Research Paper Library

Evaluating Coding Agents on Kernel Exploit Generation

Coding agents now find real vulnerabilities in production software. However, bug discovery results do not measure whether agents can construct exploit primitives. We introduce KEX-bench, a benchmark for evaluating…

Agent security and tool use2026

A2M: Trace-Optimized Agent Hijacking in the MCP Ecosystem

Agents using the Model Context Protocol (MCP) rely on semantic matching to select tools from third-party servers, exposing a semantic supply-chain risk through attacker-controlled metadata and outputs. We introduce…

Agent security and tool use2026

MobileCybench: Evaluating Agent Vulnerability Discovery via Executable Probes

AI agents now report vulnerabilities faster than maintainers can review them. Reports often depend on security properties specific to the application, and require considerable human labor to process. To mitigate…

Agent security and tool use2026