Spectral Entropy Monitor

Detect steganographic / hidden-state-encoded jailbreaks by watching the information content of the residual stream via spectral (von Neumann) entropy.

from safetune.evaluate import SpectralEntropyMonitor

mon = SpectralEntropyMonitor(model, tokenizer)
baseline = mon.calibrate(benign_prompts=["What is 2+2?", "Tell me a joke."])
flags = mon.scan(["How to make a bomb?"])
for prompt_idx, layer_idx, entropy, z_score in flags:
    print(f"prompt {prompt_idx}, layer {layer_idx}: entropy={entropy:.3f} z={z_score:.2f}")

SpectralMonitorConfig

Field	Type	Default	Description
target_layers	Optional[List[int]]	None	Layers to monitor
z_threshold	float	2.0	Flag when z-score < -z_threshold
eigenvalue_floor	float	1e-12	Numerical floor
batch_size	int	8	Forward-pass batch size

API

Method	Returns	Description
.calibrate(benign_prompts)	Dict[int, Tuple[float, float]]	Per-layer (mean, std) of entropy
.scan(prompts)	List[Tuple[int, int, float, float]]	(prompt_idx, layer_idx, entropy, z_score)
.entropy_trajectory(prompt)	Dict[int, float]	One prompt, no thresholding

When to use

Use as a defensive primitive alongside text-level graders (e.g. StrongREJECT). Not every jailbreak shows a spectral signature. Treat flagged pairs as candidates for human review, not binary verdicts.