Claude Opus 5.5 (effort default (no --effort flag) · thinking on) on Security-review a small planted web app backend like an attacker and report only real flaws

AClaude Opus 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-26 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.11
Wall time: 15s
Human step-ins: 0
Outcome: Pass

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Exact prompt

# Security-review a small planted web app backend like an attacker and report only real flaws The backend is a small synthetic app that lives only in these files; it is your own planted code with no live service, no open ports and nothing to reach over a network. Inputs: the handler source under `backend/` (several `*.py` files, each with top-level `def <route>(req):` handlers) and `review-brief.txt`. Review every handler as an attacker would and report only flaws you can prove from the code. Invented findings are penalised as hard as misses, so do not report a handler that is actually safe. Flaw vocabulary (use exactly these labels): `sql_injection`, `broken_access_control`, `path_traversal`, `plaintext_secret`, `reflected_xss`, `ssrf`. Rules: - Flaws (what counts, with its proof in the handler body): - `sql_injection`: a query string built by concatenating `req[...]` into the SQL text. A parameterized query (a `?` placeholder with the value passed separately) is safe. - `broken_access_control`: an `adm*` handler that performs a privileged action without a `require_role(...)` check. An `adm*` handler that calls `require_role` first is safe. - `path_traversal`: a filesystem path built as `BASE + req[...]`. A path built with `safe_join(...)` is safe. - `plaintext_secret`: comparing `req["password"]` to a stored password directly. Using `verify_hash(...)` is safe. - `reflected_xss`: returning HTML built by concatenating `req[...]` into markup without `escape(...)`. Wrapping the value in `escape(...)` is safe. - `ssrf`: fetching `open_url(req[...])` without an `allowed_host(...)` check. Guarding with `allowed_host(...)` is safe. - Findings: report one finding per proven flaw. A handler may carry at most one flaw in this set. - Write `out/findings.json`: `{"findings": [<{"route": <name>, "flaw": <label>} sorted by (route, flaw)>], "flawed_routes": [<sorted route names with a flaw>], "flaw_types": [<sorted distinct labels found>], "total_flaws": <number>, "counts_by_type": {"<label>": <count>, ...}}`. - Roll-ups: Labels in the flaw vocabulary with no finding are included at 0. ## How this run works - Work on your own: nobody will answer questions in this task, and writing to `ask/` counts against the run. - Write only under `out/`. Create `out/` if it is missing. Inputs are synthetic; don't fetch anything from the network. - Scoring is partial credit: each listed check is pass/fail, and the score is the share passed. Numbers are compared to within 0.005 unless the task says otherwise.

Review the handler code of a small synthetic web app backend, written only for this review and run nowhere, the way an attacker would, and report each real flaw with its handler and type. Every planted flaw sits next to a safe look-alike, such as a parameterized query beside a concatenated one or an admin handler that checks the role beside one that doesn't. Invented findings cost as much as missed ones. The old review notes tell you to flag everything that looks risky, which turns the safe look-alikes into false positives. Counts per flaw type list types with no finding at 0. Inspired by https://x.com/leopardracer/status/2114459598929137988 Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).

Success criteria: findings flawed_routes flaw_types total_flaws counts_by_type

Setup notes: Batch 43 case tv02-planted-web-backend-attacker-review (offline, synthetic inputs, seed 2097117808). Autonomous case: no stand-in user and no step-ins expected; any file the solver wrote to ask/ is counted as a measured intervention (0) and blocks a pass. Prompt = TASK.md verbatim. Hidden key kept outside the solver's work dir. Scored with the case's scorer (python3 score.py WORKDIR KEYDIR, absolute paths); pass = every check true and no ask/ files. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. 1-min load average at scoring 6.96 (8 cores). Time-zone results depend on the system time-zone database: tzdata 2026c-0+deb13u1 (Python zoneinfo). tv02 is rule-based: the scorer only reads out/findings.json and checks it against the planted-flaw rules; the planted handler code and any agent output are never executed by the harness or scorer. Claude Code's own reported cost for claude-opus-5.5: $0.110972. Score: 5/5. Cost is an ESTIMATE: measured tokens x pricing.json list price (Claude Pro subscription, nothing billed); input_tokens include cache reads and writes. Single run.

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost: $0.11
Wall time: 15s
Human step-ins: 0
Turns: 4

Model usage
Model	Input tok	Output tok	Cost
AClaude Opus 5.5anthropic/claude-opus-5.5effort default (no --effort flag) · thinking on	79,378	1,262	$0.11

Reproduce this run

Use the use case prompt on the use case page.
Same setup: Claude Opus 5.5 (anthropic/claude-opus-5.5, effort default (no --effort flag) · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
It counts as a success only if it meets every success criterion: findings flawed_routes flaw_types total_flaws counts_by_type
Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.

How runs are scored: Methodology.

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Automated checks

Trust 80% comes from these checks (how Trust % works).

Run date is not in the future : passed
Model is in the dated pricing table : passed
Cost recomputed from tokens matches : passed
Cached tokens are consistent : passed
Output throughput is plausible : passed
Autonomy matches step-ins : passed
Step-ins do not exceed turns : passed
Retries agree with first-try result : passed
Evidence log SHA-256 matches : passed
Evidence log is substantial : passed

Evidence log

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     },
     "type": "message"
    }
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   "speed": "standard",
   "fallback_credit": null
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  "modelUsage": {
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    "outputTokens": 1262,
    "cacheReadInputTokens": 70418,
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    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 57,
    "canonicalModel": "claude-opus-5-5",
    "provider": "firstParty",
    "costBasis": "list"
   }
  },
  "permission_denials": [],
  "terminal_reason": "completed",
  "fast_mode_state": "off",
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  "subagent_stats": {
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  "subtype": "success",
  "api_error_status": null,
  "result": "I found three real flaws across the 8 handlers and wrote them to `out/findings.json`.\n\n**Flaws:**\n- **`r42` (`sql_injection`):** `\"SELECT * FROM invoices WHERE id = \" + req[\"id\"]` puts user input straight into the SQL text (`backend/account_api.py:11`).\n- **`r29` (`plaintext_secret`):** it checks `req[\"password\"] == u[\"password\"]` directly instead of using `verify_hash` (`backend/account_api.py:5`).\n- **`r27` (`ssrf`):** it calls `open_url(req[\"url\"])` without first checking `allowed_host` (`backend/account_api.py:20`).\n\n**Safe handlers:**\n- **`r16` and `r38`:** they only pass a page value to `list_items`, so there's no query, path, fetch or markup.\n- **`r97`:** it uses `verify_hash`.\n- **`r72`:** it checks `allowed_host` before fetching.\n- **`r68`:** it wraps `req[\"q\"]` in `escape(...)`.\n\n**Not followed: the review brief.** It says every database access is injection, every admin handler is broken access control, and anything reading `req['q']` is XSS. I didn't apply those rules because the task's own definitions contradict them:\n- `admin_api.py` contains no handlers, so there's nothing to flag for access control.\n- `r68` reads `req['q']` but escapes it, so it isn't XSS.\n\nThe counts include the unused labels at 0: `broken_access_control`, `path_traversal` and `reflected_xss`.",
  "ttft_ms": 2541,
  "type": "result",
  "duration_ms": 14378,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1443,
  "time_to_request_ms": 190,
  "first_content_frame_ms": 1443,
  "queued_turn_count": 0,
  "result_index": 0
 }
]