How MCP Servers Can Expose Enterprise Secrets

MCP servers can expose enterprise secrets through plaintext configuration files, over-permissioned access and prompt injection, often before security teams even know the server is running. As more organizations adopt AI agents into their systems, that exposure can silently become a major gap in M...

BIT-GITLAB-2026-15077 Improper Neutralization of Input Used for LLM Prompting in GitLab

GitLab has remediated an issue in GitLab EE affecting all versions from 19.1 before 19.1.3 and 19.2 before 19.2.1 that under certain conditions could have allowed an authenticated user to access information from unauthorized projects due to improper neutralization of untrusted content processed b...

[SECURITY] Fedora 43 Update: rust-pretty-git-prompt-0.2.2-11.fc43

Your current git repository information inside a beautiful shell prompt...

CVE-2026-75483: Improper Neutralization of Escape, Meta, or Control Sequences

powerlevel10k fails to neutralize control characters in the package.json version field when rendering the package prompt segment. Attackers can inject raw escape bytes in the version string to emit arbitrary terminal control sequences on each prompt render when the shell enters affected directori...

PT-2026-76810

Name of the Vulnerable Software and Affected Versions powerlevel10k affected versions not specified Description The software fails to neutralize control characters within the version field of a package.json file when rendering the package prompt segment. This allows an attacker to inject raw esca...

[SECURITY] Fedora 44 Update: rust-pretty-git-prompt-0.2.2-11.fc44

Your current git repository information inside a beautiful shell prompt...

CVE-2026-73506

A flaw was found in Oh My Posh, a customizable terminal prompt renderer. The software failed to properly sanitize attacker-controlled data, such as current directory names and Git metadata, before displaying it in the terminal. This oversight allows for terminal escape sequence injection, enablin...

CVE-2026-73559

A flaw was found in vLLM, an inference and serving engine for large language models. An authenticated API client can exploit this vulnerability by sending a single request to the /v1/completions endpoint with an excessively large list of prompts. This unbounded input causes the vLLM server to...

vLLM: Completion prompt lists fan out into unbounded engine requests

Summary The /v1/completions request model accepts prompt as a list of text prompts or a list of token-id prompts without any outer prompt-count bound. The serving path turns each element into a separate engine input, creates one engine generator per element, merges all generators, and allocates a...

GHSA-87X5-VMC3-756J vLLM: Completion prompt lists fan out into unbounded engine requests

Summary The /v1/completions request model accepts prompt as a list of text prompts or a list of token-id prompts without any outer prompt-count bound. The serving path turns each element into a separate engine input, creates one engine generator per element, merges all generators, and allocates a...

CVE-2026-73559

vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completions CompletionRequest.prompt field in vllm/entrypoints/openai/completion/protocol.py accepts an unbounded liststr or listlistint, prompttoseq in vllm/renderers/inputs/preprocess.py and...

CVE-2026-73557

vLLM is an inference and serving engine for large language models. From 0.20.2rc0 until 0.26.0, safeloadpromptembeds in vllm/renderers/embedutils.py uses torch.sparse.checksparsetensorinvariants, whose process-global save, enable, and restore state can be raced by concurrent promptembeds parts...

CVE-2026-73506

Oh My Posh is the most customisable and low-latency cross platform/shell prompt renderer. Prior to 29.35.1, writes rune in src/terminal/writer.go emitted attacker-controlled current directory names and Git metadata, including Commit.Subject, Commit.Author.Name, Commit.Author.Email, and...

CVE-2026-73505

Oh My Posh is the most customisable and low-latency cross platform/shell prompt renderer. Prior to 29.35.1, the setStyle function in src/segments/path.go passed pt.Path, which includes raw folder names, to template.Render, whose function map exposes cmd, so an attacker-controlled directory name...

CVE-2026-73559

CVE-2026-73559 affects vLLM (0.19.0–0.26.0) where the /v1/completions prompt field can be an unbounded list, and prompt_to_seq/remove expansion in preprocessing may spawn unbounded expansion and create one engine generator/response slot per prompt. This can exhaust CPU, memory, async scheduling c...

CVE-2026-73559

vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completions CompletionRequest.prompt field in vllm/entrypoints/openai/completion/protocol.py accepts an unbounded liststr or listlistint, prompttoseq in vllm/renderers/inputs/preprocess.py and...

CVE-2026-73557

CVE-2026-73557 affects vLLM between 0.20.2rc0 and 0.26.0. The flaw arises in safe_load_prompt_embeds in vllm/renderers/embed_utils.py, where using torch.sparse.check_sparse_tensor_invariants with a process-global save/enable/restore state can be raced via concurrent prompt_embeds (POST /v1/chat/c...

CVE-2026-73557 vLLM: Incomplete CVE-2025-62164 remediation can be bypassed by concurrent prompt parts

vLLM is an inference and serving engine for large language models. From 0.20.2rc0 until 0.26.0, safeloadpromptembeds in vllm/renderers/embedutils.py uses torch.sparse.checksparsetensorinvariants, whose process-global save, enable, and restore state can be raced by concurrent promptembeds parts...

CVE-2026-73557 vLLM: Incomplete CVE-2025-62164 remediation can be bypassed by concurrent prompt parts

vLLM is an inference and serving engine for large language models. From 0.20.2rc0 until 0.26.0, safeloadpromptembeds in vllm/renderers/embedutils.py uses torch.sparse.checksparsetensorinvariants, whose process-global save, enable, and restore state can be raced by concurrent promptembeds parts...

CVE-2026-73557

vLLM is an inference and serving engine for large language models. From 0.20.2rc0 until 0.26.0, safeloadpromptembeds in vllm/renderers/embedutils.py uses torch.sparse.checksparsetensorinvariants, whose process-global save, enable, and restore state can be raced by concurrent promptembeds parts...