$ the-wire · showcase
LFM3 lands across llama.cpp and Ollama, vLLM fields four security fixes
By RepoJournal · Filed · About Local LLMs · Composed from the cited sources · methodology
LiquidAI's LFM3 family picks up first-class support in both llama.cpp and Ollama on the same day vLLM ships four security patches, three of them unauthenticated attack surfaces.
model : add LiquidAI/LFM3-1.7B and LiquidAI/LFM3-VL-2B ggml-org/llama.cpp
llama.cpp adds LiquidAI/LFM3-1.7B and LFM3-VL-2B, with video input deferred and correctness checked against the reference implementation. The companion Ollama change honors an explicit tokenizer.ggml.add_bos_token, since LFM3 GGUFs set it to false and the lfm2 default was stripping the template's BOS; on lfm2:24b, WikiText PPL drops from 81.3 to 72.0.
[Security] Fix ReDoS in validation error path sanitizer (#52120) vllm-project/vllm
vLLM patches a ReDoS in the validation error path sanitizer, one of four security fixes landing here. The other three: a sanitize_message() address regex that only matched lowercase and so failed to strip PIL's uppercase __repr__ heap addresses from responses to unauthenticated clients, a DoS via prompt embeds on XD-RoPE models that is an incomplete fix of CVE-2026-55514, and quadratic Cohere2 ...
sanitize_message() address regex is lowercase-only and does not match PIL's uppercase __repr__, leaking live heap addresses to unauthenticated clients vllm-project/vllm
The address leak is the one to size carefully: sanitize_message() was the scrubber between PIL exception text and the client, and it missed the uppercase form, so live heap addresses reached callers who never authenticated.
server: add router device memory margin parameter for dynamic unloading ggml-org/llama.cpp
llama.cpp's server adds --models-memory-margin, letting the router keep several small embedding models resident and unload them when a large text model needs the space. It behaves like the autofit memory margin, tracking per-model requirements and evicting in the existing max-number order.
[Fix] compressed-tensors: Serve split-expert MXFP4 MoE via FP4 Marlin sgl-project/sglang
A compressed-tensors mxfp4-pack-quantized MoE checkpoint with experts split per expert (experts.{e}.{gate,up,down}_proj.*, as llmcompressor emits) now loads through FP4 Marlin in SGLang; before this it failed with a KeyError on w2_weight_packed. The earlier fix covered MXFP4 dense linear only. Elsewhere: MOSS-Image packs its joint-block QKV projections for quality=high, FlashAttention calls rou...
Action items
- → Upgrade vllm to a build containing the four security commits before exposing a server to untrusted clients vllm-project/vllm [immediate]
- → Rebuild SGLang for split-expert MXFP4 MoE loading if your compressed-tensors checkpoints currently fail with KeyError... sgl-project/sglang [plan]