Suzano A.I CyberSecurity Scoring
28/03/2026
Access Monitoring Plan
Access Monitoring Plan
No incidents recorded for Suzano in 2026.
No incidents recorded for Suzano in 2026.
No incidents recorded for Suzano in 2026.
Paper and Forest Product Manufacturing
International Paper (NYSE: IP; LSE: IPC) is the global leader in sustainable packaging solutions. With company headquarters in Memphis, Tennessee, USA, and EMEA (Europe, Middle East and Africa) headquarters in London, UK, we employ more than 65,000 team members and serve customers around the world with operations in more than 30 countries. Together with our customers, we make the world safer and more productive, one sustainable packaging solution at a time. Learn more at internationalpaper.com.
Somos a maior produtora e exportadora de papéis para embalagens do Brasil, líderes nos mercados de embalagens de papelão ondulado, sacos industriais e papel-cartão e a única indústria do País a oferecer soluções em celuloses de fibra curta, fibra longa e fluff. Com mais de 120 anos de história, temos 22 unidades industriais no Brasil e uma na Argentina e uma capacidade produtiva anual de 4,5 milhões de toneladas de celulose de mercado e papéis. Toda a gestão da Klabin está orientada para o desenvolvimento sustentável e buscamos crescimento integrado e responsável, que une rentabilidade, desenvolvimento social e compromisso ambiental. Desde 2014 integramos o Índice de Sustentabilidade Empresarial (ISE) da B3 e, desde 2020, o Índice Dow Jones Best-in-Class, com participação na carteira Global e de Mercados Emergentes. Saiba mais sobre a nossa atuação em klabin.com.br. ⚠️ Atenção! A Klabin e seus parceiros de recrutamento não cobram qualquer valor dos candidatos em seus processos seletivos.
APP serves as the holding company for multiple Indonesia pulp and paper manufacturing as well as forestry entities, catering to the increasing global need for high-quality tissue, packaging, and paper. Our products reach over 150 countries spanning six continents. APP Group serves as group name of pulp, paper and forestry entities under APP and its affiliates including the pulp and paper and forestry operation in China. Driven by a dedication to sustainability and ethical practices, we prioritize the well-being of our employees, society, and environment. Our approach involves harnessing technological advancements and fostering innovation, collaborating closely with communities, and upholding internationally recognized business and operational standards throughout our production and supply chain. Aligned with the Environmental, Social, and Governance (ESG) principles, our Sustainability Roadmap Vision 2030 steers our actions toward safeguarding environment, bolstering local communities, preserving biodiversity, and striving for carbon neutrality in all our endeavors.
Headquartered in Singapore, RGE is a global group of companies in the bio-based resources and energy sectors, serving over 100 markets worldwide. With more than US$40 billion in assets and a workforce of 80,000 employees, our operations span across Indonesia, China, Brazil, Canada, Spain, and Malaysia. As a global leader in sustainable natural fibres, edible oils, green packaging, and cleaner energy solutions, we play a vital role in feeding, clothing, and improving the lives of billions every day. We build lasting businesses by integrating sustainability as an enabler of growth, while advancing a nature-positive, greener future. Established in 1973, we have remained committed to sustainable development, conservation, and community empowerment, guided by our 5Cs philosophy of doing what is good for the Community, Country, Climate, Customer, and only then will it be good for the Company.
Latest updates, reports, and threat intel affecting the global network.
At the Woodspin factory, a joint venture with Brazilian pulp producer Suzano, Spinnova implementing its technology on an industrial scale...
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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