MCG A.I CyberSecurity Scoring
29/04/2026
Access Monitoring Plan
Access Monitoring Plan
No incidents recorded for Motion Consulting Group in 2026.
No incidents recorded for Motion Consulting Group in 2026.
No incidents recorded for Motion Consulting Group in 2026.
We are at the forefront of digital transformation in the Americas, positively impacting the lives of over 500 million people. As a key player in emerging industries, we drive innovation and change through ambitious modernization projects and cutting-edge solutions. By understanding the region's challenges and demands, we provide a comprehensive portfolio of business solutions tailored to the primary industries, driving innovation and success in the market. We operate in 13 countries with a dedicated team of over 15,000 regional employees, earning the trust of more than 5,000 corporate clients to lead their digital transformation journeys. Our extensive presence spans Argentina, Brazil, Chile, Colombia, Costa Rica, Guatemala, Ecuador, the United States, Canada, Mexico, Panama, Peru, and Uruguay.
Computacenter is a leading independent technology and services provider, trusted by large corporate and public sector organisations. We are a responsible business that believes in winning together for our people and our planet. We help our customers to Source, Transform and Manage their technology infrastructure to deliver digital transformation, enabling people and their business. Computacenter plc is a public company quoted on the London Stock Exchange (CCC.L) and a member of the FTSE 250. Computacenter employs over 21,000 people worldwide.
In a world undergoing constant change, VINCI Energies contributes to the environmental transition by helping bring about major trends in the digital landscape and energy sector. VINCI Energies’ teams roll out technologies and integrate customised multi-technical solutions, from design to implementation, operation and maintenance. With their strong local roots and agile and innovative structure, VINCI Energies’ 2,100 business units have positioned themselves at the heart of the energy choices of their customers, boosting the reliability, efficiency and sustainability of their infrastructure and processes. VINCI Energies strives for global performance, caring for the planet, useful to people and committed to local communities. 2024: €20.4 billion // 102,600 employees // 2,100 Business Units // 61 countries
We are a global technology consultancy that delivers extraordinary impact by blending design, engineering and AI expertise. For 30 years, our commitment to design-led thinking, engineering excellence and innovation means we prioritize people, build teams with strong technical foundations and embed AI into every step of the process – not just as a tool but as a mindset. It’s this approach that sets us apart, sparks bold ideas and empowers us to drive real, lasting innovation. We’re not preparing for the future – we’re defining it.
LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 700 clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by 86,000+ talented and entrepreneurial professionals across more than 30 countries, LTIMindtree — a Larsen & Toubro Group company — combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale. LTIMindtree is proud to be an equal opportunity employer. We are committed to providing equal employment opportunities regardless of race, ethnicity, nationality, gender, gender identity, gender expression, language, age, sexual orientation, religion, marital status, veteran status, socio-economic status, disability, or any other characteristic protected by applicable law. Please note that neither LTIMindtree nor any of its authorized recruitment agencies/partners charge candidates any registration fees or other fees for appearing in interviews or securing employment/internships. Candidates are solely responsible for verifying the credentials of any agency or consultant claiming to work with LTIMindtree for recruitment purposes. Please note that anyone relying on representations made by fraudulent employment agencies/consultant does so at their own risk. LTIMindtree disclaims any liability for loss or damage suffered as a result of such actions. For more info, please visit ltimindtree.com.
Latest updates, reports, and threat intel affecting the global network.
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A vulnerability recently detected in hospital robots could have given anyone access to live photos, videos and medical records within a ...
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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