What is the official website of TJDFT ?

The official website of TJDFT is http://www.tjdft.jus.br.

What is TJDFT's cybersecurity risk score?

TJDFT has an AI-generated cybersecurity risk score of 758 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has TJDFT experienced?

According to Rankiteo, TJDFT currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has TJDFT been affected by any supply chain cyber incidents ?

According to Rankiteo, TJDFT has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.

Does TJDFT have SOC 2 Type 1 certification ?

According to Rankiteo, TJDFT is not certified under SOC 2 Type 1.

Does TJDFT have SOC 2 Type 2 certification ?

According to Rankiteo, TJDFT does not hold a SOC 2 Type 2 certification.

Does TJDFT comply with GDPR ?

According to Rankiteo, TJDFT is not listed as GDPR compliant.

Does TJDFT have PCI DSS certification ?

According to Rankiteo, TJDFT does not currently maintain PCI DSS compliance.

Does TJDFT comply with HIPAA ?

According to Rankiteo, TJDFT is not compliant with HIPAA regulations.

Does TJDFT have ISO 27001 certification ?

According to Rankiteo,TJDFT is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does TJDFT operate in ?

TJDFT operates primarily in the Administration of Justice industry.

How many employees does TJDFT have ?

TJDFT employs approximately 3,345 people worldwide.

Does TJDFT own any subsidiaries ?

TJDFT presently has no subsidiaries across any sectors.

How many LinkedIn followers does TJDFT have ?

TJDFT's official LinkedIn profile has approximately 10,021 followers.

What is the NAICS classification code for TJDFT ?

TJDFT is classified under the NAICS code 92211, which corresponds to Courts.

Does TJDFT have a Crunchbase profile ?

No, TJDFT does not have a profile on Crunchbase.

Does TJDFT have a LinkedIn profile ?

Yes, TJDFT maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/tjdft.

How many cybersecurity incidents has TJDFT experienced ?

As of June 23, 2026, Rankiteo reports that TJDFT has experienced 1 cybersecurity incidents.

How many peer or competitor companies does TJDFT have ?

TJDFT has an estimated 374 peer or competitor companies worldwide.

What types of cybersecurity incidents has TJDFT faced ?

Incident Types: The types of cybersecurity incidents that have occurred include Cyber Attack.

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TJDFT

Boost Score +25 with badge (5 left)

758

/1000

Fair

783

/1000

Fair

TJDFT Vendor Cyber Rating & Cyber Score

jus.br

Add Your Compliance Badge

O Tribunal de Justiça do Distrito Federal e dos Territórios (TJDFT) foi criado em 21 abril de 1960, no mesmo dia da inauguração de Brasília. Nossa missão é garantir os direitos do cidadão e a paz social por meio da solução célere, transparente e ética dos conflitos. O que fazemos? O TJDFT é responsável por aplicar a lei e resolver os conflitos no âmbito do Distrito Federal e dos Territórios. É composto por duas instâncias ou dois graus de jurisdição. A 1ª Instância ou 1º Grau é a porta de entrada da maioria dos processos no TJDFT e representa cerca de 80% dos processos distribuídos anualmente no Tribunal. É na 1ª Instância que os juízes analisam e julgam as ações apresentadas à Justiça do DF, como por exemplo: pedidos de

TJDFT A.I CyberSecurity Scoring

Scoring History

TJDFT

TJDFT CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

TJDFT

Cyber Attack

100

08/2022

TJD123171022

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A.I.

TJDFT Company Scoring based on AI Models

Cyber Incidents Likelihood 3 - 6 - 9 months

Actual

Prediction

Incident Predictions locked

Access Monitoring Plan

A.I Risk Score Likelihood 3 - 6 - 9 months

Actual

Prediction A

Prediction B

Prediction C

Prediction D

A.I. Risk Score Predictions locked

Access Monitoring Plan

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Underwriter Stats for TJDFT

Incidents vs Administration of Justice Industry Avg (This Year)

No incidents recorded for TJDFT in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for TJDFT in 2026.

Incident Types TJDFT vs Administration of Justice Industry Avg (This Year)

No incidents recorded for TJDFT in 2026.

Incident History - TJDFT (X = Date, Y = Severity)

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SUBSIDIARY

TJDFT Subsidiaries

Parent Company

TJDFT

Administration of Justice

Website: http://www.tjdft.jus.br

Company Size: 5,001-10,000 employees

No subsidiary data available for this company.

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TJDFT Similar Companies

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NEWS

TJDFT CyberSecurity News

Latest updates, reports, and threat intel affecting the global network.

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CVE

Latest

Global CVEs (Not Company-Specific)

CVE-2026-54236

SUMMARY

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.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 5.3)

cvss3

Base Score: 5.3

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N

Impact Score

1.4

Exploitability

3.9

REFERENCES

CVE-2026-54235

SUMMARY

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.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: )

cvss4

Base Score: 6.9

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

Impact Score

Exploitability

REFERENCES

CVE-2026-54233

SUMMARY

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.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 6.5)

cvss3

Base Score: 6.5

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Impact Score

3.6

Exploitability

2.8

REFERENCES

CVE-2026-54232

SUMMARY

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.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 8.8)

cvss3

Base Score: 8.8

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Impact Score

5.9

Exploitability

2.8

REFERENCES

https://github.com/vllm-project/vllm/security/advisories/GHSA-jrf6-vqxq-pjv2

CVE-2026-53923

SUMMARY

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.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: )

cvss4

Base Score: 5.3

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

Impact Score

Exploitability

REFERENCES

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