CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: netfilter: arp_tables: fix IEEE1394 ARP payload parsing Weiming Shi says: "arp_packet_match() unconditionally parses the ARP payload assuming two hardware addresses are present (source and target). However, IPv4-over-IEEE1394 ARP (RFC 2734) omits the target hardware address field, and arp_hdr_len() already accounts for this by returning a shorter length for ARPHRD_IEEE1394 devices. As a result, on IEEE1394 interfaces arp_packet_match() advances past a nonexistent target hardware address and reads the wrong bytes for both the target device address comparison and the target IP address. This causes arptables rules to match against garbage data, leading to incorrect filtering decisions: packets that should be accepted may be dropped and vice versa. The ARP stack in net/ipv4/arp.c (arp_create and arp_process) already handles this correctly by skipping the target hardware address for ARPHRD_IEEE1394. Apply the same pattern to arp_packet_match()." Mangle the original patch to always return 0 (no match) in case user matches on the target hardware address which is never present in IEEE1394. Note that this returns 0 (no match) for either normal and inverse match because matching in the target hardware address in ARPHRD_IEEE1394 has never been supported by arptables. This is intentional, matching on the target hardware address should never evaluate true for ARPHRD_IEEE1394. Moreover, adjust arpt_mangle to drop the packet too as AI suggests: In arpt_mangle, the logic assumes a standard ARP layout. Because IEEE1394 (FireWire) omits the target hardware address, the linear pointer arithmetic miscalculates the offset for the target IP address. This causes mangling operations to write to the wrong location, leading to packet corruption. To ensure safety, this patch drops packets (NF_DROP) when mangling is requested for these fields on IEEE1394 devices, as the current implementation cannot correctly map the FireWire ARP payload. This omits both mangling target hardware and IP address. Even if IP address mangling should be possible in IEEE1394, this would require to adjust arpt_mangle offset calculation, which has never been supported. Based on patch from Weiming Shi .

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE Other	No informations.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V3.1	5.5	MEDIUM	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H More informations Base: Exploitabilty Metrics The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component. Attack Vector This metric reflects the context by which vulnerability exploitation is possible. Local The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Attack Complexity This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability. Low Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success when attacking the vulnerable component. Privileges Required This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability. Low The attacker requires privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources. User Interaction This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable component. None The vulnerable system can be exploited without interaction from any user. Base: Scope Metrics The Scope metric captures whether a vulnerability in one vulnerable component impacts resources in components beyond its security scope. Scope Formally, a security authority is a mechanism (e.g., an application, an operating system, firmware, a sandbox environment) that defines and enforces access control in terms of how certain subjects/actors (e.g., human users, processes) can access certain restricted objects/resources (e.g., files, CPU, memory) in a controlled manner. All the subjects and objects under the jurisdiction of a single security authority are considered to be under one security scope. If a vulnerability in a vulnerable component can affect a component which is in a different security scope than the vulnerable component, a Scope change occurs. Intuitively, whenever the impact of a vulnerability breaches a security/trust boundary and impacts components outside the security scope in which vulnerable component resides, a Scope change occurs. Unchanged An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority. Base: Impact Metrics The Impact metrics capture the effects of a successfully exploited vulnerability on the component that suffers the worst outcome that is most directly and predictably associated with the attack. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve. Confidentiality Impact This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability. None There is no loss of confidentiality within the impacted component. Integrity Impact This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. None There is no loss of integrity within the impacted component. Availability Impact This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability. High There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable). Temporal Metrics The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence in the description of a vulnerability. Environmental Metrics These metrics enable the analyst to customize the CVSS score depending on the importance of the affected IT asset to a user’s organization, measured in terms of Confidentiality, Integrity, and Availability.	nvd@nist.gov

EPSS

EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.

EPSS Score

The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.

EPSS Percentile

The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.

EPSS First.org