# exploit-primitives
5 articlestagged with “exploit-primitives”
LLM Internals for Exploit Developers
Transformer architecture, tokenizer internals, logit pipelines, and trust boundaries from an offensive security perspective.
Exploiting Attention Mechanisms
How the self-attention mechanism in transformers can be leveraged to steer model behavior, hijack information routing, and bypass safety instructions.
Embedding Space Attacks
Techniques for attacking the embedding layer of LLMs, including adversarial perturbations, embedding inversion, and semantic space manipulation.
LLM Internals & Exploit Primitives
An overview of large language model architecture from a security researcher's perspective, covering the key components that create exploitable attack surfaces.
Tokenization-Based Attacks
How tokenizer behavior creates exploitable gaps between human-readable text and model-internal representations, enabling filter bypass and payload obfuscation.