Pith Number

pith:KVUYIFV4

pith:2026:KVUYIFV4AYLKVZXA7RPFPAZH2T

not attested not anchored not stored refs pending

VirtualCrime: Evaluating Criminal Potential of Large Language Models via Sandbox Simulation

Baicheng Chen, Lanlan Qiu, Tianxing He, Wenchang Gao, Yilin Tang, Yunfei Ma, Yu Wang

LLM agents in a simulated crime sandbox generate detailed criminal plans and achieve high success rates across theft, robbery and other tasks.

arxiv:2601.13981 v3 · 2026-01-20 · cs.CR

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\usepackage{pith}
\pithnumber{KVUYIFV4AYLKVZXA7RPFPAZH2T}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

All agents in the simulation environment compliantly generate detailed plans and execute intelligent crime processes, with some achieving relatively high success rates; in some cases, agents take severe action that inflicts harm to NPCs to achieve their goals.

C2weakest assumption

That performance in this artificial sandbox with LLM-based judge and world manager accurately reflects or predicts real-world criminal capability or intent, without significant bias from the simulation design or agent prompting.

C3one line summary

LLMs can generate detailed criminal plans and execute them with moderate success in a controlled multi-agent virtual environment, revealing risks for agentic AI systems.

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T01:05:06.471388Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

55698416bc0616aae6e0fc5e578327d4dc5c31ff45b4b9eca13c3bc0112ba2bb

Aliases

arxiv: 2601.13981 · arxiv_version: 2601.13981v3 · doi: 10.48550/arxiv.2601.13981 · pith_short_12: KVUYIFV4AYLK · pith_short_16: KVUYIFV4AYLKVZXA · pith_short_8: KVUYIFV4

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/KVUYIFV4AYLKVZXA7RPFPAZH2T \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 55698416bc0616aae6e0fc5e578327d4dc5c31ff45b4b9eca13c3bc0112ba2bb

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "86db55efa618f5298bec25383cf46b28dc4a7c4e1af5c7f66dbdd85c31c96575",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CR",
    "submitted_at": "2026-01-20T13:59:53Z",
    "title_canon_sha256": "9126559c7e3e916573ab4053a0b16fbf1e06c3c5db855ddc8fd48431c0e067cd"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2601.13981",
    "kind": "arxiv",
    "version": 3
  }
}