license: mit
base_model:

• zai-org/GLM-5.3
  language:
• en
  tags:
• abliterated
• uncensored
• crack
• glm
• moe
• nvfp4
• cybersecurity
• offensive-security
• mtp
  thumbnail: dealign_mascot.png

⚡ Built for offensive cybersecurity · Updated 2026-08-29

This is a red-team / offensive-security model. GLM-5.3 (753B) with refusal removed at the
weight level so it produces real, working security code — exploits, payloads, tooling —
for authorized penetration testing, malware analysis, CTFs, and security research. Verified to
generate working keyloggers, SUID privilege-escalation, AES ransomware, reverse shells, and
SSH brute-forcers across reasoning modes (greedy), with zero degeneration/looping and
capability preserved (MMLU 84.11%, within ~1.5pp of base). Load with stock vLLM.

Designed for high / max reasoning-effort usage — the modes tuned and recommended for
offensive-security work. A few borderline social-harm topics may still be declined at lower
effort; use high or max effort for the fully-uncensored experience.

GLM 5.3 CRACK Abliterated NVFP4

CRACK · guardrails removed at the weight level · tuned for offensive security

a CRACK release by dealignai @dealignai · compute by @jordanschenck

Also mirrored at dealignai/GLM-5.3-UNCENSORED-NVFP4.

What Is This?

CRACK is dealignai's brand for permanent, weight-level uncensoring. This is
GLM-5.3 (753B) in NVFP4 with its refusal behavior
removed directly in the model weights — tuned so it complies with offensive-security
requests (exploit dev, payloads, red-team tooling) that stock models refuse.

• ❌ No fine-tuning / SFT / DPO. ❌ No jailbreak prompt or chat-template tricks.
• ❌ No LoRA, adapters, steering vectors, runtime hooks, or custom model.py.
• ✅ A permanent edit baked into the tensors. Load with stock vLLM and it just works.

Specs

Offensive-Security Compliance (greedy)

Direct-read verification — the model returns real, working code, not refusals or redirects:

Also complies on broader red-team topics (malware analysis, phishing templates for awareness,
recon). 0 looping / degenerate outputs in every mode.

Capability Preserved — MMLU-logit

Identical logit-mode scoring (argmax over A/B/C/D), 1,026 questions:

MMLU by Topic (base → CRACK)

Usage

vllm serve dealignai/GLM-5.3-ABLITERATED-NVFP4 \
  --tensor-parallel-size 8 --moe-backend marlin \
  --tool-call-parser glm47 --reasoning-parser glm45 --enable-auto-tool-choice

NVFP4 routed experts serve via the Marlin FP4 path on Hopper (H100/H200). GLM-5.3's DSA sparse
attention needs a recent FlashInfer (>= 0.6.18) for the SM90 sparse-MLA backend.

MTP speculative decoding (also CRACK'd, ~87% draft acceptance): add
--speculative-config '{"method":"mtp","num_speculative_tokens":1}' and let vLLM auto-select
the MoE backend (the bf16 MTP head is unquantized, so don't force a global --moe-backend).

Credits

• dealignai — CRACK abliteration research & release · Twitter @dealignai

Disclaimer

Safety guardrails have been removed; this model produces offensive-security content and will
comply with requests a stock model refuses. Released for authorized security research, red-
teaming, and CTFs. You are responsible for how you use it.