CVE-2022-48998

Score / Severity

7.8

High

CVE Descriptions

powerpc/bpf/32: Fix Oops on tail call tests

In the Linux kernel, the following vulnerability has been resolved: powerpc/bpf/32: Fix Oops on tail call tests test_bpf tail call tests end up as: test_bpf: #0 Tail call leaf jited:1 85 PASS test_bpf: #1 Tail call 2 jited:1 111 PASS test_bpf: #2 Tail call 3 jited:1 145 PASS test_bpf: #3 Tail call 4 jited:1 170 PASS test_bpf: #4 Tail call load/store leaf jited:1 190 PASS test_bpf: #5 Tail call load/store jited:1 BUG: Unable to handle kernel data access on write at 0xf1b4e000 Faulting instruction address: 0xbe86b710 Oops: Kernel access of bad area, sig: 11 [#1] BE PAGE_SIZE=4K MMU=Hash PowerMac Modules linked in: test_bpf(+) CPU: 0 PID: 97 Comm: insmod Not tainted 6.1.0-rc4+ #195 Hardware name: PowerMac3,1 750CL 0x87210 PowerMac NIP: be86b710 LR: be857e88 CTR: be86b704 REGS: f1b4df20 TRAP: 0300 Not tainted (6.1.0-rc4+) MSR: 00009032 CR: 28008242 XER: 00000000 DAR: f1b4e000 DSISR: 42000000 GPR00: 00000001 f1b4dfe0 c11d2280 00000000 00000000 00000000 00000002 00000000 GPR08: f1b4e000 be86b704 f1b4e000 00000000 00000000 100d816a f2440000 fe73baa8 GPR16: f2458000 00000000 c1941ae4 f1fe2248 00000045 c0de0000 f2458030 00000000 GPR24: 000003e8 0000000f f2458000 f1b4dc90 3e584b46 00000000 f24466a0 c1941a00 NIP [be86b710] 0xbe86b710 LR [be857e88] __run_one+0xec/0x264 [test_bpf] Call Trace: [f1b4dfe0] [00000002] 0x2 (unreliable) Instruction dump: XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX XXXXXXXX ---[ end trace 0000000000000000 ]--- This is a tentative to write above the stack. The problem is encoutered with tests added by commit 38608ee7b690 ("bpf, tests: Add load store test case for tail call") This happens because tail call is done to a BPF prog with a different stack_depth. At the time being, the stack is kept as is when the caller tail calls its callee. But at exit, the callee restores the stack based on its own properties. Therefore here, at each run, r1 is erroneously increased by 32 - 16 = 16 bytes. This was done that way in order to pass the tail call count from caller to callee through the stack. As powerpc32 doesn't have a red zone in the stack, it was necessary the maintain the stack as is for the tail call. But it was not anticipated that the BPF frame size could be different. Let's take a new approach. Use register r4 to carry the tail call count during the tail call, and save it into the stack at function entry if required. This means the input parameter must be in r3, which is more correct as it is a 32 bits parameter, then tail call better match with normal BPF function entry, the down side being that we move that input parameter back and forth between r3 and r4. That can be optimised later. Doing that also has the advantage of maximising the common parts between tail calls and a normal function exit. With the fix, tail call tests are now successfull: test_bpf: #0 Tail call leaf jited:1 53 PASS test_bpf: #1 Tail call 2 jited:1 115 PASS test_bpf: #2 Tail call 3 jited:1 154 PASS test_bpf: #3 Tail call 4 jited:1 165 PASS test_bpf: #4 Tail call load/store leaf jited:1 101 PASS test_bpf: #5 Tail call load/store jited:1 141 PASS test_bpf: #6 Tail call error path, max count reached jited:1 994 PASS test_bpf: #7 Tail call count preserved across function calls jited:1 140975 PASS test_bpf: #8 Tail call error path, NULL target jited:1 110 PASS test_bpf: #9 Tail call error path, index out of range jited:1 69 PASS test_bpf: test_tail_calls: Summary: 10 PASSED, 0 FAILED, [10/10 JIT'ed]

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-787	Out-of-bounds Write The product writes data past the end, or before the beginning, of the intended buffer.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V3.1	7.8	HIGH	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/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. High There is a total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server. Integrity Impact This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. High There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to 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.

Date	EPSS V0	EPSS V1	EPSS V2 (> 2022-02-04)	EPSS V3 (> 2025-03-07)	EPSS V4 (> 2025-03-17)
2024-10-22	–	–	–	0.04%	–
2024-12-08	–	–	–	0.04%	–
2025-02-16	–	–	–	0.04%	–
2025-01-19	–	–	–	0.04%	–
2025-02-16	–	–	–	0.04%	–
2025-03-18	–	–	–	–	0.03%
2025-03-30	–	–	–	–	0.02%
2025-04-06	–	–	–	–	0.03%
2025-04-15	–	–	–	–	0.02%
2025-04-16	–	–	–	–	0.03%
2025-04-16	–	–	–	–	0.03,%

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

Date	Percentile
2024-10-22	1%
2024-12-08	11%
2025-02-16	12%
2025-01-19	11%
2025-02-16	12%
2025-03-18	4%
2025-03-30	3%
2025-04-06	4%
2025-04-15	4%
2025-04-16	6%
2025-04-16	6%