CPS A.I CyberSecurity Scoring
23/03/2026
Access Monitoring Plan
Access Monitoring Plan
No incidents recorded for Crown Prosecution Service in 2026.
No incidents recorded for Crown Prosecution Service in 2026.
No incidents recorded for Crown Prosecution Service in 2026.
DLA Piper is a global law firm helping our clients achieve their goals wherever they do business. Our pursuit of innovation has transformed our delivery of legal services. With offices in the Americas, Europe, the Middle East, Africa and Asia Pacific, we deliver exceptional outcomes on cross-border projects, critical transactions and high-stakes disputes. Every day we help trailblazing organizations seize business opportunities and successfully manage growth and change at speed. Through our pro bono work and community investment around the world, we help create a more just and sustainable future. Visit dlapiper.com to discover more.
Latest updates, reports, and threat intel affecting the global network.
The Public Prosecution Service (OM) is looking into a large-scale cyberattack at telecom provider Odido, which resulted in the theft of...
A gang of fraudsters who used 'SMS blasters' to scam commuters out of thousands of pounds have been sentenced, following a BTP...
Morocco's Public Prosecutors Office continued to expand the digital transformation of the justice system in 2024.
The UK Foreign Office recently revealed that a Chinese hacking group, known as Storm 1849, successfully infiltrated the UK Home Office's...
Chinese money laundering - A Chinese national has been sentenced for orchestrating a £5 billion money laundering operation involving.
Currently in preventive detention at the Rebeuss House of Arrest and Correction, M...
The head of MI5, the UK's domestic security service, revealed that its spies had disrupted a new threat from China in recent days,...
Labour MP and chair of security committee Matt Western says there are 'a lot of questions yet to be asked'
LONDON – Chinese hackers accessed classified British computer systems for more than a decade, sources familiar with the matter said, as.
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, the fix for CVE-2026-22778, which introduced a sanitize_message helper that strips object-repr memory addresses from error messages before they reach the client, is incomplete: several response paths echo str(exc) directly to clients without calling sanitize_message. The unsanitized sites include the Anthropic API router in vllm/entrypoints/anthropic/api_router.py (the POST /v1/messages and POST /v1/messages/count_tokens handlers), the Server-Sent Events streaming converter in vllm/entrypoints/anthropic/serving.py, and the realtime speech-to-text WebSocket in vllm/entrypoints/speech_to_text/realtime/connection.py. These paths catch the exception inside the route coroutine and construct the JSONResponse themselves, bypassing the sanitizing global FastAPI exception handler, and WebSocket frames do not traverse that handler chain at all. Using the same primitive as the parent issue, an unauthenticated attacker can send malformed image bytes through the Anthropic Messages API image content parts so that PIL.Image.open raises an UnidentifiedImageError whose message contains the BytesIO object repr, leaking the heap memory address verbatim in the error.message field of the response body. This vulnerability is fixed in 0.23.1rc0.
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, vLLM's /v1/audio/transcriptions endpoint limits compressed upload size but not decoded PCM output. A 25MB OPUS file expands to ~14.9GB of float32 PCM at decode time. This vulnerability is fixed in 0.23.1rc0.
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusion attack through the flashinfer-jit-cache package. The package is installed from a custom index (flashinfer.ai/whl/) using --extra-index-url, but the package name was not registered on PyPI, and UV_INDEX_STRATEGY="unsafe-best-match" is set globally. An attacker who registers flashinfer-jit-cache on PyPI with version 0.6.11.post2 can execute arbitrary code as root during the Docker build and backdoor every resulting container image, enabling exfiltration of all user prompts, API credentials, and model data from production vLLM deployments This vulnerability is fixed in 0.22.1.
vLLM is an inference and serving engine for large language models (LLMs). From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels (csrc/quantization/gguf/gguf_kernel.cu) causes partial tensor processing. The output tensor is allocated at full size via torch::empty (uninitialized memory), but the dequantize CUDA kernel processes only a truncated number of elements. The unfilled portion of the output tensor retains whatever was previously in GPU memory. In multi-tenant inference deployments, this residual GPU memory may contain tensor data from other users' inference requests, constituting information disclosure. This vulnerability is fixed in 0.23.1rc0.
curl -i -X GET 'https://api.rankiteo.com/underwriter-getcompany-history?
linkedin_id=axa' -H 'apikey: YOUR_API_KEY_HERE'
Every week, Rankiteo analyzes billions of signals to give organizations a sharper, faster view of emerging risks. With deeper, more actionable intelligence at their fingertips, security teams can outpace threat actors, respond instantly to Zero-Day attacks, and dramatically shrink their risk exposure window.
Rankiteo is a unified scoring and risk platform that analyzes billions of signals weekly to help organizations gain faster, more actionable insights into emerging threats. Empowering teams to outpace adversaries and reduce exposure.