What is the official website of Machine Learning ?

The official website of Machine Learning is https://aws.amazon.com/machine-learning/.

What is Machine Learning's cybersecurity risk score?

Machine Learning has an AI-generated cybersecurity risk score of 752 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has Machine Learning experienced?

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

Has Machine Learning been affected by any supply chain cyber incidents ?

According to Rankiteo, Machine Learning has been affected by multiple supply chain cyber incidents. The affected supply chain sources and their corresponding incident IDs are: Amazon Web Services (AWS) (Incident ID: HEAAMA1782153018) LiteLLM (Incident ID: LIT1783694475) SimpleHelp Ltd (Incident ID: SIM1781576629) npm, Inc. (Incident ID: ELAGITAMAOPENPM1780050263) Laravel (Incident ID: LAR1782311560) Socket (Incident ID: AWSSOC1778833973) Braintrust (Incident ID: AMAUSE1778092688) Amazon Web Services (AWS) (Incident ID: LIMAMA1777312775) Vercel (Incident ID: AMAVERGITSTR1775204764) Amazon Web Services (AWS) (Incident ID: AMASTA1775118743) Aqua Security (Incident ID: AQUUSEAMASALCIS1775046662) Amazon Web Services (AWS) (Incident ID: EUR1774635987) Amazon Web Services (AWS) (Incident ID: SALAMAMICPINRED1774269319) NPM (Incident ID: GOOAMANPMGIT1773319158) Amazon Web Services (AWS) (Incident ID: RELLEX1772562253) Amazon Web Services (AWS) (Incident ID: EUR1774628727) Amazon (Incident ID: AMAAPPMIC1770935300) ConnectWise (Incident ID: SMASIMCONAMADAT1775551328) Cisco (Incident ID: CISSAI1773859283) Amazon (Incident ID: LASAMA1769009064) LinkedIn (Incident ID: LINAWS1766995316) Microsoft Security (Incident ID: AMAORAMIC1770695748) Amazon Web Services (AWS) (Incident ID: AMAAWS1770152164) Cisco (Incident ID: SAL5732257091825) Wiz (Incident ID: AMAWIZ1768515615) NPM (Incident ID: GOONPMORGGOVAPPMETTHEAWSTIKK7-1773672350) Fortinet (Incident ID: FORCISAMAJPM1767748297)

Does Machine Learning have SOC 2 Type 1 certification ?

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

Does Machine Learning have SOC 2 Type 2 certification ?

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

Does Machine Learning comply with GDPR ?

According to Rankiteo, Machine Learning is not listed as GDPR compliant.

Does Machine Learning have PCI DSS certification ?

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

Does Machine Learning comply with HIPAA ?

According to Rankiteo, Machine Learning is not compliant with HIPAA regulations.

Does Machine Learning have ISO 27001 certification ?

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

Which industry does Machine Learning operate in ?

Machine Learning operates primarily in the IT Services and IT Consulting industry.

How many employees does Machine Learning have ?

Machine Learning employs approximately None employees people worldwide.

Does Machine Learning own any subsidiaries ?

Machine Learning presently has no subsidiaries across any sectors.

How many LinkedIn followers does Machine Learning have ?

Machine Learning's official LinkedIn profile has approximately 1,322 followers.

What is the NAICS classification code for Machine Learning ?

Machine Learning is classified under the NAICS code 5415, which corresponds to Computer Systems Design and Related Services.

Does Machine Learning have a Crunchbase profile ?

No, Machine Learning does not have a profile on Crunchbase.

Does Machine Learning have a LinkedIn profile ?

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

How many cybersecurity incidents has Machine Learning experienced ?

As of August 3, 2026, Rankiteo reports that Machine Learning has experienced 74 cybersecurity incidents.

How many peer or competitor companies does Machine Learning have ?

Machine Learning has an estimated 41,233 peer or competitor companies worldwide.

What types of cybersecurity incidents has Machine Learning faced ?

Incident Types: The types of cybersecurity incidents that have occurred include Breach, Data Leak, Cyber Attack, Ransomware and Vulnerability.

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Machine Learning

Boost Score +25 with badge (5 left)

752

/1000

Fair

777

/1000

Fair

Machine Learning Vendor Cyber Rating & Cyber Score

amazon.com

Add Your Compliance Badge

Machine Learning A.I CyberSecurity Scoring

Scoring History

Machine Learning

Machine Learning CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Amazon Science

Vulnerability

100

7/2026

AMAORATUXROC178...

Amazon Science

Vulnerability

7/2026

ANYWINGOOAMAAUG...

Amazon

Vulnerability

6/2026

AMA1782498585

Amazon Web Services...

Vulnerability

6/2026

AMA1782541446

Amazon Web Services...

Vulnerability

6/2026

Amazon Web Serv...

HEAAMA178215301...

Amazon

Vulnerability

100

6/2026

ANTAMA178355044...

Amazon Web Services...

Vulnerability

6/2026

LiteLLM

LIT1783694475

AWS Startups

Vulnerability

100

6/2026

SimpleHelp Ltd

SIM1781576629

Amazon Web Services...

Cyber Attack

100

6/2026

GOOAMA178116664...

Amazon Web Services...

Cyber Attack

5/2026

npm, Inc.

ELAGITAMAOPENPM...

Amazon Science

Vulnerability

5/2026

OPEANTAMAXAI177...

Amazon Web Services...

Vulnerability

100

5/2026

Laravel

LAR1782311560

AWS for Healthcare ...

Cyber Attack

5/2026

Socket

AWSSOC177883397...

Amazon Science

Breach

5/2026

Braintrust

AMAUSE177809268...

Amazon Web Services...

Vulnerability

100

5/2026

APPGOOAMA178163...

Amazon Web Services...

Cyber Attack

4/2026

Amazon Web Serv...

LIMAMA177731277...

Amazon

Cyber Attack

4/2026

ELFTEMCOUGRUAMA...

Amazon Web Services...

Cyber Attack

4/2026

Vercel

AMAVERGITSTR177...

Amazon Web Services...

Vulnerability

100

4/2026

Amazon Web Serv...

AMASTA177511874...

AWS Partners

Vulnerability

4/2026

AWSGITSTR177516...

Amazon Web Services...

Vulnerability

100

4/2026

Aqua Security

AQUUSEAMASALCIS...

Amazon Web Services...

Vulnerability

100

3/2026

DELMICAMAFORSPL...

Amazon Web Services...

Cyber Attack

3/2026

Amazon Web Serv...

EUR1774635987

Amazon Web Services...

Vulnerability

100

3/2026

Amazon Web Serv...

SALAMAMICPINRED...

Amazon Web Services...

Vulnerability

3/2026

AMA1773707045

Amazon Web Services...

Cyber Attack

3/2026

NPM

GOOAMANPMGIT177...

Amazon Web Services...

Vulnerability

3/2026

AMA1772792723

Amazon Web Services...

Cyber Attack

100

3/2026

AMA1772678135

Amazon Web Services...

Breach

100

3/2026

Amazon Web Serv...

RELLEX177256225...

Amazon

Cyber Attack

3/2026

AMA1775744757

Amazon Web Services...

Breach

3/2026

Amazon Web Serv...

EUR1774628727

Amazon

Vulnerability

100

2/2026

Amazon

AMAAPPMIC177093...

Amazon

Cyber Attack

2/2026

ConnectWise

SMASIMCONAMADAT...

Amazon

Breach

2/2026

AMA1770339008

Amazon

Cyber Attack

2/2026

AMAINSCOIGOOFLI...

Amazon

Cyber Attack

2/2026

AMA1773987972

AWS Partners

Breach

1/2026

AWSDIGOVH176978...

Amazon

Vulnerability

100

1/2026

Cisco

CISSAI177385928...

Amazon

Cyber Attack

1/2026

Amazon

LASAMA176900906...

AWS Databases & Ana...

Cyber Attack

1/2026

HUNAWS177273537...

Amazon Web Services...

Vulnerability

100

1/2026

GOOAMAOPEANT177...

AWS Partners

Cyber Attack

12/2025

LINAWS176699531...

Amazon Web Services...

Cyber Attack

100

12/2025

Microsoft Secur...

AMAORAMIC177069...

Amazon

Vulnerability

12/2025

AMAUNIGOOWAK176...

Amazon Web Services...

Cyber Attack

100

12/2025

KUBNVITENALIAMA...

Amazon Web Services...

Breach

100

11/2025

Amazon Web Serv...

AMAAWS177015216...

Amazon Web Services...

Cyber Attack

11/2025

AMA1765965358

AWS Databases & Ana...

Cyber Attack

100

11/2025

AWS1783621498

Machine Learning

Cyber Attack

100

10/2025

AMA023220210212...

Machine Learning

Cyber Attack

9/2025

AMA409264009232...

AWS Partners

Cyber Attack

100

9/2025

Cisco

SAL573225709182...

Amazon Web Services...

Vulnerability

100

9/2025

Wiz

AMAWIZ176851561...

For Industries

Vulnerability

8/2025

NPM

GOONPMORGGOVAPP...

Machine Learning

Cyber Attack

7/2025

RIN709072225

Machine Learning

Vulnerability

6/2025

AMA505082225

Machine Learning

Ransomware

100

5/2025

AMA503215011212...

Amazon Web Services...

Vulnerability

100

12/2024

Fortinet

FORCISAMAJPM176...

Machine Learning

Vulnerability

8/2024

AMA000082124

Machine Learning

Breach

7/2024

AMA000072524

Machine Learning

Cyber Attack

100

6/2024

AMA190211910222...

Machine Learning

Breach

09/2023

WHO04111223

Machine Learning

Vulnerability

6/2023

AMA016210111072...

Machine Learning

Data Leak

10/2021

TWI19174123

Amazon Web Services...

Cyber Attack

100

6/2021

AMA1768595116

Machine Learning

Breach

100

01/2021

RIN01518622

Amazon Web Services...

Cyber Attack

100

6/2020

AMA1780793273

Machine Learning

Data Leak

01/2020

AMA21461222

Machine Learning

Data Leak

01/2020

RIN211261222

Machine Learning

Data Leak

12/2019

RIN2178523

Amazon Web Services...

Vulnerability

3/2019

AMA1781685326

Amazon

Breach

6/2018

TIKAMA176901658...

Machine Learning

Data Leak

02/2018

AMA350181223

Machine Learning

Breach

3/2017

WHO631090125

Machine Learning

Cyber Attack

01/2016

AMA0417522

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A.I.

Machine Learning 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

Loading…

Underwriter Stats for Machine Learning

Incidents vs IT Services and IT Consulting Industry Avg (This Year)

No incidents recorded for Machine Learning in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Machine Learning in 2026.

Incident Types Machine Learning vs IT Services and IT Consulting Industry Avg (This Year)

No incidents recorded for Machine Learning in 2026.

Incident History - Machine Learning (X = Date, Y = Severity)

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SUBSIDIARY

Machine Learning Subsidiaries

Machine Learning

IT Services and IT Consulting

Website: https://aws.amazon.com/machine-learning/

Company Size: None employees

AmazonSoftware Development

TwitchSoftware Development

Twitch AdsInternet Publishing

Whole Foods MarketRetail

Whole Planet Philanthropic Fundraising Services

Whole KidsPhilanthropy

Whole CitiesNon-profit Organizations

Amazon ScienceResearch Services

Amazon AdsAdvertising Services

Amazon Lab126Computers and Electronics Manufacturing

Souq.comTechnology, Information and Internet

GoodreadsTechnology, Information and Internet

Amazon Fulfillment Technologies & RoboticsSoftware Development

Zappos Family of CompaniesRetail

IMDb.comEntertainment Providers

AudibleSoftware Development

Audible GmbHOnline Audio and Video Media

Sell on AmazonTechnology, Information and Internet

Amazon GamesEntertainment Providers

Amazon PayTechnology, Information and Internet

Amazon MusicEntertainment Providers

ShopbopRetail

Amazon BusinessRetail

Amazon DesignInternet Publishing

RingComputers and Electronics Manufacturing

Amazon ClinicHospitals and Health Care

Amazon AssociatesTechnology, Information and Internet

Alexa AutoMotor Vehicle Manufacturing

A9.comTechnology, Information and Internet

Alexa.comTechnology, Information and Internet

Amazon KindleRetail

Amazon Development Center PolandSoftware Development

Amazon Alexa DevelopersComputers and Electronics Manufacturing

Transportation, Shipping, & Logistics at AmazonTransportation, Logistics, Supply Chain and Storage

Amazon FashionRetail Apparel and Fashion

Fulfillment by AmazonWarehousing and Storage

Amazon Appstore DevelopersConsumer Electronics

Amazon LaunchpadInternet Publishing

AbeBooks, an Amazon companyTechnology, Information and Internet

CurseComputer Games

Just Walk Out technologyRetail

Woot, Inc.Retail

Quidsi Inc., a subsidiary of AmazonRetail

Wag.comManufacturing

Soap.comRetail

BeautyBar.comRetail

Casa.comRetail

YoYo.comConsumer Goods

Buy with PrimeInternet Publishing

Comixology, an Amazon companyEntertainment

Annapurna LabsComputer Networking

AWS ThinkboxSoftware Development

CreateSpaceBook and Periodical Publishing

Amazon | LiquavistaAppliances, Electrical, and Electronics Manufacturing

Amazon PharmacyRetail Pharmacies

LOVEFiLMEntertainment Providers

Amazon Ads PartnersAdvertising Services

Amazon TodayTechnology, Information and Internet

Brilliance PublishingBook and Periodical Publishing

Amazon Web Services (AWS)IT Services and IT Consulting

AWS Training & CertificationIT Services and IT Consulting

AWS AIIT Services and IT Consulting

AWS CareersIT Services and IT Consulting

AWS Machine LearningIT Services and IT Consulting

AWS Executive InsightsInformation Technology & Services

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Machine Learning Similar Companies

T-Systems International

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Your digitalization partner with industry expertise With locations in more than 26 countries and over 26,000 employees (2024), T-Systems is one of the leading providers of digital services in Europe. The Deutsche Telekom subsidiary is headquartered in Germany and has a presence in Europe as well as in selected core markets and strategic production locations. T-Systems can provide a global production and supply chain to companies operating worldwide. T-Systems offers integrated end-to-end IT solutions, driving the digital transformation of companies in all industries and the public sector. T-Systems’ focus industries are automotive, the public sector, healthcare and transport. For these areas, T-Systems develops industryspecific solutions – so-called vertical applications. The comprehensive portfolio of services includes secure operation of traditional IT infrastructures, migration to private cloud and public cloud environments of hyperscalers, as well as management of hybrid and multi-cloud infrastructures. T-Systems integrates customized platforms, industry-specific applications and innovative technologies such as artificial intelligence (AI), big data and blockchain into these infrastructures. To achieve this, the Telekom subsidiary works closely with leading global technology partners. The end-to-end services also include state-of-the-art security solutions and data protection in accordance with DSGVO requirements. T-Systems pursues a holistic approach: consulting (advisory) and solutions from the areas of digital, cloud services and security are offered from a single source. Become one of us: https://www.t-systems.com/de/en/company/careers Imprint: https://www.t-systems.com/de/en/imprint

Dimension Data

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Ingram Micro

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Ingram Micro is a leading technology company for the global information technology ecosystem. With the ability to reach nearly 90% of the global population, we play a vital role in the worldwide IT sales channel, bringing products and services from technology manufacturers and cloud providers to a highly diversified base of business-to-business technology experts. Through Ingram Micro Xvantage™, our AI-powered digital platform, we offer what we believe to be the industry’s first comprehensive business-to-consumer-like experience, integrating hardware and cloud subscriptions, personalized recommendations, instant pricing, order tracking, and billing automation. We also provide a broad range of technology services, including financing, specialized marketing, and lifecycle management, as well as technical pre- and post-sales professional support. Learn more at www.ingrammicro.com.

Appen

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Appen has been a leader in AI training data for over 25 years, providing high-quality, diverse datasets that power the world's leading AI models. Our end-to-end platform, deep expertise, and scalable human-in-the-loop services enable AI innovators to build and optimize cutting-edge models. We specialize in creating bespoke, human-generated data to train, fine-tune, and evaluate AI models across multiple domains, including generative AI, large language models (LLMs), computer vision, speech recognition, and more. Our solutions support critical AI functions such as supervised fine-tuning, reinforcement learning with human feedback (RLHF), model evaluation, and bias mitigation. Our advanced AI-assisted data annotation platform, combined with a global crowd of more than 1M contributors in over 200 countries, ensures the delivery of accurate and diverse datasets. Our commitment to quality, scalability, and ethical AI practices makes Appen a trusted partner for enterprises aiming to develop and deploy effective AI solutions. At Appen, we foster a culture of innovation, collaboration, and excellence. We value curiosity, accountability, and a commitment to delivering the highest-quality AI solutions. We support work-life balance with flexible work arrangements and a dynamic, results-driven environment. Employees have access to competitive pay, comprehensive benefits, and opportunities for continuous learning and career growth. Our team works closely with the world’s top technology companies and enterprises, tackling exciting challenges and shaping the future of artificial intelligence.

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NEWS

Machine Learning CyberSecurity News

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

March 18, 2026 05:51 AM

Emerging Growth Patterns Driving Expansion in the Adversarial Machine Learning Market

The adversarial machine learning market is on the brink of remarkable expansion, driven by rapid advancements in AI applications and...

Read Article

March 18, 2026 05:39 AM

AI vs ransomware: High-stakes cybersecurity showdown

Ransomware has evolved into one of the most disruptive cyber threats globally, affecting sectors ranging from healthcare and finance to...

Read Article

March 17, 2026 01:34 PM

AI Cyberattacks Rising: How Hackers Use Machine Learning to Launch Smarter Attacks

AI cyberattacks are rapidly transforming the cybersecurity landscape, enabling attackers to automate and scale operations with unprecedented...

Read Article

March 16, 2026 09:47 PM

What is Adversarial AI? Understanding Poisoned Model Attacks As AI becomes more integrated into our daily lives and critical systems, the security of these models is more important than ever. This video explores the concept of Adversarial AI and how attacke

Read Article

March 13, 2026 02:25 AM

International Cybersecurity Agencies Issue Joint Guidance on AI and Machine Learning Supply Chain Risks

Cybersecurity agencies from eight countries have released joint guidance outlining risks and mitigation strategies for artificial...

Read Article

February 24, 2026 08:00 AM

How to Prepare for Machine Learning Security Risks

Machine learning systems are vulnerable to a variety of dangers. These include model theft, system hijacking, data poisoning, and evasion attacks.

Read Article

February 16, 2026 08:00 AM

Making sense of AI’s role in cyber security

Cyber security companies have jumped on the AI bandwagon. We look at where artificial intelligence is a useful add-on and where it poses...

Read Article

February 16, 2026 08:00 AM

Techie Tonic: The rise of next-gen security information and event management

Explore the evolution of Security Information and Event Management (SIEM) as it integrates AI and machine learning to enhance cybersecurity.

Read Article

February 14, 2026 08:00 AM

Machine Learning for Cybersecurity: Best Practices and Tips

TL;DR: Machine Learning in cybersecurity has revolutionized how organizations defend against constantly evolving threats.

Read Article

Loading…

CVE

Latest

Global CVEs (Not Company-Specific)

CVE-2026-18577

SUMMARY

An incomplete patch for CVE-2026-18556 allows for authentication bypass and account takeover in N-central Versions through 2026.3.1

Published

Date2026-08-02

Updated

Date2026-08-02

RISK INFORMATION (Score: )

cvss4

Base Score: 8.2

Complexity: HIGH

CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:L/SI:L/SA:L/E:A/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-2026-10848

SUMMARY

The OCPP 1.6 client in subsys/net/lib/ocpp parsed inbound WAMP RPC frames in parse_rpc_msg() (subsys/net/lib/ocpp/ocpp_j.c) using a hand-rolled helper, extract_string_field(), that copied the message's uid and action fields with strncpy(out_buf, token + 1, outlen - 1) and then scanned the result with strchr(out_buf, '"'). Because strncpy does not NUL-terminate the destination when the source is at least outlen - 1 (127) bytes long, the subsequent strchr reads past the 128-byte destination buffer into adjacent stack memory; if a " byte is found beyond the buffer, a one-byte out-of-bounds NUL write also occurs. A related defect in extract_payload() runs strchr/strrchr over the receive buffer, which may not be NUL-terminated when a maximal-length frame fills it. The parsed bytes come directly from the OCPP central-system server over a websocket: the reader thread fills recv_buf via websocket_recv_msg() and calls parse_rpc_msg() on each inbound DATA frame (subsys/net/lib/ocpp/ocpp.c). A malicious or compromised central server, or an on-path attacker (OCPP is commonly deployed over plain ws://), can send an RPC frame whose uid or action field is 127+ bytes with no closing quote, triggering the out-of-bounds access. The primary impact is a remotely triggerable denial of service: the unbounded scan can fault on an unmapped page, and the stray NUL write can corrupt adjacent stack state. The over-read data is not reflected to the peer, so disclosure is limited. The feature is EXPERIMENTAL and must be explicitly enabled (CONFIG_OCPP). The fix replaces the manual parser with the bounds-respecting json_mixed_arr_parse() and copies the extracted uid with an explicitly NUL-terminated buffer, eliminating both over-reads.

Published

Date2026-08-02

Updated

Date2026-08-02

RISK INFORMATION (Score: 7)

cvss3

Base Score: 7.0

Complexity: HIGH

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

Impact Score

4.7

Exploitability

2.2

REFERENCES

CVE-2026-9856

SUMMARY

A vulnerability in huggingface/transformers versions <=5.8.0.dev0 allows an attacker to perform arbitrary file writes via path traversal. The issue resides in the `save_pretrained()` methods of `PreTrainedTokenizerBase` and `ProcessorMixin`, where keys from the `chat_template` dictionary are used directly as filenames without proper validation. An attacker can exploit this by publishing a malicious Hugging Face Hub repository with a crafted `tokenizer_config.json` file. When a victim downloads and saves the tokenizer or processor, the attacker-controlled keys can escape the intended save directory, enabling arbitrary file writes with attacker-controlled content. This vulnerability affects multiple processors inheriting from `ProcessorMixin`, including Idefics, Florence, Gemma, Phi, and Qwen-VL.

Published

Date2026-08-02

Updated

Date2026-08-02

RISK INFORMATION (Score: 7.1)

cvss3

Base Score: 7.1

Complexity: LOW

CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:L

Impact Score

4.2

Exploitability

2.8

REFERENCES

CVE-2026-65321

SUMMARY

PyAthena prior to 3.35.4 contains a sql injection vulnerability that allows unauthenticated attackers to inject arbitrary SQL by exploiting improper quote-escaping in DefaultParameterFormatter.format(), which routes DELETE and CTAS statements to the _escape_hive function that backslash-escapes single quotes rather than doubling them. Because Athena and Trino do not treat backslashes as escape characters inside string literals, attacker-supplied input such as a single quote followed by SQL syntax causes the parser to terminate the string literal prematurely, enabling data exfiltration via UNION SELECT, execution of destructive statements, and attacker-controlled CTAS destination and content.

Published

Date2026-08-02

Updated

Date2026-08-02

RISK INFORMATION (Score: 9.8)

cvss3

Base Score: 9.8

Complexity: LOW

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

cvss4

Base Score: 9.3

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/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

5.9

Exploitability

3.9

REFERENCES

CVE-2026-10774

SUMMARY

Zephyr's Bluetooth Mesh subnet key management leaks one PSA Crypto key slot on every subnet-key teardown. In subsys/bluetooth/mesh/subnet.c, net_keys_create() imports the Private Beacon Key into a PSA key slot under CONFIG_BT_MESH_PRIV_BEACONS (enabled by default), but subnet_keys_destroy() guarded the matching psa_destroy_key() with CONFIG_BT_MESH_V1d1. That Kconfig symbol was removed when explicit Mesh 1.0.1 support was dropped, so the destroy branch became permanently dead code and the import is never balanced by a destroy. The imbalanced teardown is reached every time subnet keys are destroyed: deleting a subnet (Config Server NetKey Delete), completing a Key Refresh Procedure (which retires the old key set), and resetting/re-provisioning the node. The over-the-air triggers are processed only under the node's device key, so they are exercisable by the provisioner or network administrator that owns the node, reachable over the Bluetooth Mesh network. With the default CONFIG_MBEDTLS_PSA_KEY_SLOT_COUNT of 16, repeated add/delete or key-refresh cycles exhaust the shared PSA key-slot pool after roughly a dozen rounds. Once exhausted, bt_mesh_private_beacon_key() and thus subnet creation fail: the node can no longer add subnets or complete key refresh, and other PSA crypto consumers on the device may be starved, until the device is rebooted. The fix aligns the destroy guard with the import guard (CONFIG_BT_MESH_PRIV_BEACONS) so each slot is freed.

Published

Date2026-08-02

Updated

Date2026-08-02

RISK INFORMATION (Score: 2.4)

cvss3

Base Score: 2.4

Complexity: LOW

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

Impact Score

1.4

Exploitability

0.9

REFERENCES

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