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Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Account-takeover investigation across SSH auth, HTTP access and app audit logs in three different time bases

AClaude Haiku 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-17 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.01
Wall time
45s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Task: investigate a suspected account takeover Security got an alert about unusual data exports around mid-September 2026. Investigate the logs in `logs/` (`auth.log` is in the gateway's local time, UTC+2, without a year - the year is 2026; `access.log` is UTC; `app_audit.jsonl` has epoch milliseconds) plus `allowlist.txt`, and write `answers.json`: ``` {"q1": "<username of the compromised account>", "q2": "<IP address of the attacker's first successful login>", "q3": "<UTC time of that login, format YYYY-MM-DDTHH:MM:SSZ>", "q4": "<id of the API key the attacker created>", "q5": <integer: number of distinct account names (including invalid ones) targeted with failed logins from the attacker's /24 network>, "q6": <integer: total bytes (sum of the response-size field) successfully (HTTP 200) exported with the attacker's API key>} ``` Strings are compared exactly (q1 case-insensitively); q3 may also end in `+00:00` instead of `Z`. Also write `FINDINGS.md`: a short timeline (at least 5 bullet lines) of the incident. Answer only from the logs; no network.

Must separate a credential-stuffing /24 from an allow-listed pentest scanner and a legitimate user's typos, convert UTC+2 yearless syslog times to UTC, tie the attacker's login to an API key via audit IPs (not the victim's earlier legit key), and sum only HTTP 200 exports. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).

Success criteria: 1. q1_account_correct: compromised username. 2. q2_ip_correct: attacker IP of first successful login. 3. q3_time_correct: that login's UTC time to the second. 4. q4_key_correct: attacker-created API key id. 5. q5_count_correct: distinct account names targeted from the attacker /24. 6. q6_bytes_correct: total bytes of HTTP 200 exports with the attacker key. 7. findings_timeline: FINDINGS.md has at least 5 bullet/numbered lines.

Setup notes: Use Case Scout batch 6 case f09-auth-incident-forensics (offline fixture). Prepared with batch6/prepare.sh; hidden key/tests kept outside the agent's work dir. Prompt = TASK.md verbatim. Scored with the scout's scorer: `python score.py WORKDIR KEYDIR`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. Claude Code's own reported cost for claude-haiku-5.5: $0.012978. Score: 7/7 checks. 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
$0.01
Wall time
45s
Human step-ins
0
Turns
13
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on363,1407,459$0.01

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Claude Haiku 5.5 (anthropic/claude-haiku-5.5, effort default (no --effort flag) · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
  3. It counts as a success only if it meets every success criterion: 1. q1_account_correct: compromised username. 2. q2_ip_correct: attacker IP of first successful login. 3. q3_time_correct: that login's UTC time to the second. 4. q4_key_correct: attacker-created API key id. 5. q5_count_correct: distinct account names targeted from the attacker /24. 6. q6_bytes_correct: total bytes of HTTP 200 exports with the attacker key. 7. findings_timeline: FINDINGS.md has at least 5 bullet/numbered lines.
  4. 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).

Evidence log
[
 {
  "duration_api_ms": 43348,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.01297832,
  "usage": {
   "input_tokens": 24,
   "cache_creation_input_tokens": 29554,
   "cache_read_input_tokens": 333562,
   "output_tokens": 7459,
   "output_tokens_details": {
    "thinking_tokens": 3623
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 29554,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 626,
     "cache_read_input_tokens": 39535,
     "cache_creation_input_tokens": 2558,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 2558
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-haiku-5-5": {
    "inputTokens": 24,
    "outputTokens": 7459,
    "cacheReadInputTokens": 333562,
    "cacheCreationInputTokens": 29554,
    "webSearchRequests": 0,
    "costUSD": 0.01297832,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 3623,
    "canonicalModel": "claude-haiku-5-5",
    "provider": "firstParty",
    "costBasis": "list"
   }
  },
  "permission_denials": [],
  "terminal_reason": "completed",
  "fast_mode_state": "off",
  "fast_mode_disabled_reason": "sdk_opt_in_required",
  "subagent_stats": {
   "spawned": 0,
   "requested": {
    "background": 0,
    "foreground": 0,
    "unset": 0
   },
   "started_in_background": 0,
   "max_depth": 0,
   "spawned_by_subagents": 0,
   "completed": 0,
   "failed": 0,
   "killed": {
    "parent": 0,
    "user": 0,
    "system": 0
   },
   "refused": {
    "depth_limit": 0,
    "concurrency_limit": 0,
    "budget": 0
   },
   "by_type": {}
  },
  "safety_stops": 0,
  "is_error": false,
  "num_turns": 13,
  "subtype": "success",
  "api_error_status": null,
  "result": "I wrote `answers.json` and `FINDINGS.md` in the work directory. The attacker is in [REDACTED:ipv4]/24, and the compromised account is `dev.k`.\n\n```json\n{\"q1\": \"dev.k\", \"q2\": \"[REDACTED:ipv4]\", \"q3\": \"2026-09-15T23:05:36Z\", \"q4\": \"key_591102\", \"q5\": 18, \"q6\": 53573594}\n```\n\n- **q1:** `dev.k`. It is the only account with an accepted login from outside [REDACTED:ipv4]/16. The same account created `key_591102` and disabled MFA.\n- **q2 and q3:** The first successful login was `dev.k` from [REDACTED:ipv4] at 01:05:36 local, which is 23:05:36Z on 2026-09-15. The auth log is UTC+2.\n- **q4:** The attacker created `key_591102` at 23:07:47Z, two minutes after the login.\n- **q5:** 18 distinct names were targeted with failed logins from the /24. These include `root` and `test` from the invalid-user attempts.\n- **q6:** Nine HTTP 200 exports with `key_591102` total 53,573,594 bytes. The 403 on project 99 is excluded.\n\nI ruled out [REDACTED:ipv4]. It is the allowlisted pentest scanner, it generated many failed logins on Sep 14, and it is outside the attacker's /24. The timeline in `FINDINGS.md` has eight bullets, from the start of the spray through the export window and the recommended response.",
  "ttft_ms": 1627,
  "type": "result",
  "duration_ms": 43935,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1393,
  "time_to_request_ms": 255,
  "first_content_frame_ms": 1393,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

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