CVE-2021-42059: n/a UEFI firmware stack overflow

CISO Take

This is a stack-based buffer overflow in the DisplayTypeDxe DXE driver of Insyde's InsydeH2O UEFI firmware, used as the BIOS/UEFI base by numerous OEMs (NetApp and Siemens have issued their own advisories referencing this exact issue). It is not an AI/ML-specific vulnerability — the 'ml_library' tagging on this CVE appears to be a classification error, since the flaw sits entirely at the firmware layer, below the OS and any AI/ML stack. The practical risk is low right now: EPSS is 0.35% (72nd percentile, meaning most scored CVEs sit even lower, but the absolute exploitation probability is small), it is not in CISA KEV, and there is no public exploit or Nuclei template. The real concern for a CISO is scope of exposure — firmware-level RCE is high-impact and can survive OS reimaging — on any physical host running affected InsydeH2O versions, including servers hosting training clusters or edge AI inference devices. Action: inventory devices for InsydeH2O Kernel 5.0-5.4 below the patched builds (05.08.41, 05.16.41, 05.26.41, 05.35.41, 05.42.20) via your OEM's advisory (Insyde SA-2022006), and apply vendor BIOS/UEFI updates through normal patch management — this does not warrant AI-specific incident response.

Sources:NVDEPSSinsyde.comsecurity.netapp.comcert-portal.siemens.com

What is the risk?

Low near-term exploitation likelihood: EPSS 0.35% (72nd percentile), no CISA KEV listing, no public exploit code, and no scanner/Nuclei template available. However, the underlying vulnerability class (firmware-level stack overflow leading to arbitrary code execution) is high-severity by nature — UEFI/DXE-level compromise typically requires local/physical access or a compromised update mechanism, but grants persistence beneath the OS, defeating most endpoint security tooling and surviving reinstalls. Exposure is a function of whether affected InsydeH2O-based hardware (servers, workstations, edge devices) is in the environment, not of any AI/ML software choice.

How does the attack unfold?

Initial Access

Attacker obtains local, physical, or firmware-update-channel access to a device running an affected InsydeH2O UEFI build.

Exploitation

Attacker triggers the stack-based buffer overflow in the DisplayTypeDxe DXE driver during boot to hijack execution flow.

Persistence

Malicious firmware code is planted at the UEFI level, surviving OS reinstalls and evading OS-level security tooling.

Impact

Full compromise of the underlying compute host, potentially enabling downstream tampering with any AI/ML workloads or data running on that hardware.

Initial Access

Attacker obtains local, physical, or firmware-update-channel access to a device running an affected InsydeH2O UEFI build.

Exploitation

Attacker triggers the stack-based buffer overflow in the DisplayTypeDxe DXE driver during boot to hijack execution flow.

Persistence

Malicious firmware code is planted at the UEFI level, surviving OS reinstalls and evading OS-level security tooling.

Impact

Full compromise of the underlying compute host, potentially enabling downstream tampering with any AI/ML workloads or data running on that hardware.

What systems are affected?

Package	Ecosystem	Vulnerable Range	Patched
n/a	—	—	No patch

Do you use n/a? You're affected.

How severe is it?

CVSS 3.1

N/A

EPSS

0.3%

chance of exploitation in 30 days

Higher than 28% of all CVEs

Source: EPSS v3 — FIRST.org

Exploitation Status

No known exploitation

Sophistication

Advanced

What should I do?

1 step

1) Inventory hardware/firmware versions across data center and edge fleets to identify InsydeH2O Kernel 5.0-5.4 builds prior to 05.08.41/05.16.41/05.26.41/05.35.41/05.42.20. 2) Obtain and apply the OEM-specific BIOS/UEFI update referencing Insyde advisory SA-2022006 (check NetApp and Siemens advisories if using their hardware). 3) Prioritize patching for AI training/inference hosts and edge devices where firmware compromise would be hardest to detect and most damaging to data/model integrity. 4) Restrict physical and low-level administrative access to hosts pending patching, since exploitation of DXE drivers typically requires local or privileged access. 5) No AI-specific detection is applicable — treat as standard firmware patch management.

How is it classified?

Code ExecutionInference

Which compliance frameworks are affected?

This CVE is relevant to:

NIST AI RMF

GOVERN 1.5-Risk management processes address AI system supply chain and infrastructure risks

Frequently Asked Questions

What is CVE-2021-42059?

This is a stack-based buffer overflow in the DisplayTypeDxe DXE driver of Insyde's InsydeH2O UEFI firmware, used as the BIOS/UEFI base by numerous OEMs (NetApp and Siemens have issued their own advisories referencing this exact issue). It is not an AI/ML-specific vulnerability — the 'ml_library' tagging on this CVE appears to be a classification error, since the flaw sits entirely at the firmware layer, below the OS and any AI/ML stack. The practical risk is low right now: EPSS is 0.35% (72nd percentile, meaning most scored CVEs sit even lower, but the absolute exploitation probability is small), it is not in CISA KEV, and there is no public exploit or Nuclei template. The real concern for a CISO is scope of exposure — firmware-level RCE is high-impact and can survive OS reimaging — on any physical host running affected InsydeH2O versions, including servers hosting training clusters or edge AI inference devices. Action: inventory devices for InsydeH2O Kernel 5.0-5.4 below the patched builds (05.08.41, 05.16.41, 05.26.41, 05.35.41, 05.42.20) via your OEM's advisory (Insyde SA-2022006), and apply vendor BIOS/UEFI updates through normal patch management — this does not warrant AI-specific incident response.

Is CVE-2021-42059 actively exploited?

No confirmed active exploitation of CVE-2021-42059 has been reported, but organizations should still patch proactively.

How to fix CVE-2021-42059?

1) Inventory hardware/firmware versions across data center and edge fleets to identify InsydeH2O Kernel 5.0-5.4 builds prior to 05.08.41/05.16.41/05.26.41/05.35.41/05.42.20. 2) Obtain and apply the OEM-specific BIOS/UEFI update referencing Insyde advisory SA-2022006 (check NetApp and Siemens advisories if using their hardware). 3) Prioritize patching for AI training/inference hosts and edge devices where firmware compromise would be hardest to detect and most damaging to data/model integrity. 4) Restrict physical and low-level administrative access to hosts pending patching, since exploitation of DXE drivers typically requires local or privileged access. 5) No AI-specific detection is applicable — treat as standard firmware patch management.

What systems are affected by CVE-2021-42059?

This vulnerability affects the following AI/ML architecture patterns: training pipelines, model serving.

What is the CVSS score for CVE-2021-42059?

No CVSS score has been assigned yet.

What is the AI security impact?

Affected AI Architectures

training pipelinesmodel serving

Compliance Controls Affected

NIST AI RMF: GOVERN 1.5

What are the technical details?

Original Advisory

An issue was discovered in Insyde InsydeH2O Kernel 5.0 before 05.08.41, Kernel 5.1 before 05.16.41, Kernel 5.2 before 05.26.41, Kernel 5.3 before 05.35.41, and Kernel 5.4 before 05.42.20. A stack-based buffer overflow leads toarbitrary code execution in UEFI DisplayTypeDxe DXE driver.

Exploitation Scenario

An adversary with local administrative access, physical access, or the ability to deliver a malicious firmware/BIOS update to a target machine triggers the stack-based buffer overflow in the DisplayTypeDxe DXE driver during boot, achieving arbitrary code execution at the UEFI firmware level before the OS or any security agent loads. On an AI training server or edge inference appliance, this would let the attacker implant firmware-level persistence that survives OS reinstalls, potentially enabling later tampering with model files, training data pipelines, or credentials used to access ML infrastructure — but the attack itself exploits firmware, not any AI component.