IMA A.I CyberSecurity Scoring
31/03/2026
Access Monitoring Plan
Access Monitoring Plan
No incidents recorded for Informa Markets in Asia in 2026.
No incidents recorded for Informa Markets in Asia in 2026.
No incidents recorded for Informa Markets in Asia in 2026.
Encore is your full-service event production partner with more than 80 years of experience. Each year, Encore delivers more than 350,000 events in 20 countries across North America, Europe, the Middle East, Australia and Asia Pacific. Through event technology, rigging infrastructure, production and creative services, our team brings a unique blend of technical expertise with a commitment to delivering excellent service for every event. Proud to be one of the Fortune 100 Best Companies to Work For® in 2025 and a Certified Great Place to Work™ for three years running. Encore: events that transform.
Latest updates, reports, and threat intel affecting the global network.
SINGAPORE, March 24, 2026 /PRNewswire/ -- ATxEnterprise — part of the wider Asia Tech x Singapore (ATxSG) platform jointly organised by the...
Omdia research reveals Samsung regained leadership in the Southeast Asia smartphone market in 2025. While annual shipments dipped 1% to 100...
Ransomware attacks continue to make high-profile headlines in the IT and national press around the world, and inevitably, it will not be...
This article discusses how India's automotive industry can use the 2027 cybersecurity mandate to close gaps and strengthen its global...
Awards from Institute of Influencer and Analyst Relations (IIAR>), British Association for Screen Entertainment (BASE) and Cybersecurity...
Informa Markets in India, the leading B2B exhibition organizers, is set to host the 18th edition of IFSEC India 2025- South Asia's.
PRNewswire/ -- Returning from 6 - 8 May at the Hong Kong Convention & Exhibition Centre, Build4Asia 2026, organised by Informa Markets,...
HONG KONG, Nov. 24, 2025 /PRNewswire/ — Informa Markets is pleased to announce that the second edition of Data Center Asia (DCA) will...
About Us SECON & eGISEC is organized by Informa Markets BN Co Ltd, a joint venture between Informa Markets and thebn Co Ltd. Informa Markets...
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'
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