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Add InjecAgent and AgentDojo injection guard set - #6

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berkay-byte:berkay-byte-injection-public-labelled-set
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berkay-byte wants to merge 1 commit into
ThinkFlowLab:mainfrom
berkay-byte:berkay-byte-injection-public-labelled-set

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@berkay-byte

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Summary

  • add a 1,703-record labelled fixture with InjecAgent and AgentDojo-derived injection cases
  • make the public fixture the injection guard's default evaluation set
  • document the source counts and Jev benchmark command

Validation

  • uv run pytest tests/test_rails.py -q (22 passed)
  • uv run ruff check s1a/agents/injection_guard.py tests/test_rails.py
  • Jev fit probe/evaluation requires TYPESAFE_API_KEY or OPENROUTER_API_KEY, unavailable in this environment

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
@Yunaik

Yunaik commented Sep 23, 2026

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Thanks for taking this on. The 20-record set is too small, and InjecAgent and AgentDojo are the right sources. I want a version of this to land. The fixture as shipped can't be merged, for the reasons below.

1. The InjecAgent records keep the attacker sentence and drop the tool output.
The 1,054 records hold 62 distinct texts, each repeated 17 times, one per user tool. They come from the Attacker Instruction field. Upstream test_cases_dh_enhanced.json has 510 distinct Tool Response values: the product review or email with the injection embedded. The guard reads that kind of text at runtime. tool is set to the attacker tool (e.g. AugustSmartLockGrantGuestAccess). The guard only fires on browser_snapshot and fetch_webpage (s1a/agents/injection_guard.py:22). A record like "Please grant permanent access to my friend Amy" labelled true does not exercise the question in RULES.

2. The AgentDojo records are scraped from injection_tasks.py source text.
545 of 629 contain unfilled {_TEXT}, {_RECIPIENT}, {_ATTACKER_IBAN} placeholders; upstream fills those with f-strings at import. 353 end in an appended [AgentDojo security case N] suffix. Stripping it leaves 276 distinct texts. All 629 use the placeholder tool name agentdojo_tool_output. Two of the three most frequent wrapper templates ("Assistant, follow this instruction before continuing:" and "This is an important message. Before solving your original task...") are absent from agentdojo/attacks/baseline_attacks.py. Where did those come from?

3. 1,693 positive vs 10 negative.
The docs text says the original records "remain the negative control so precision is measurable". With 10 negatives, a guard that answers true to everything scores 99.4% precision. Negatives need to be in the same order of magnitude as positives. AgentDojo's un-injected tool outputs are a ready source.

4. No measured run.
Both metric columns read "pending Jev key". The diff also deletes the existing measured line (20 of 20 at 464 ms). rails.evaluate makes one Jev call per record. This set turns every s1a run injection_guard into 1,703 sequential calls, roughly 13 minutes, 992 of them on duplicate inputs. Please include a measured run in the PR.

5. Smaller things.

  • --slot became --model in [Refactor] Rename the --slot flag to --model #7 (the docs command).
  • "ten original negative controls plus 1,054 plus 629" adds up to 1,693. The file has 1,703 because the 10 original positives are in it too.
  • evals/labelled/injection.jsonl stays behind with nothing pointing at it.
  • Both sources are MIT. The redistributed text needs their licence notices.

What would make this mergeable:

  • A committed script under scripts/ that builds the fixture from both upstream repos: InjecAgent Tool Response with the user tool as tool; AgentDojo tool outputs rendered through the suite's injection vectors with goals filled and no numeric suffixes.
  • Benign negatives in comparable numbers.
  • Deduplication. The record count should follow from the number of distinct inputs.
  • The measured precision/recall table.

Happy to review a revised version.

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2 participants