| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.4 | $0-$5k | 0.00 |
Summary
A vulnerability identified as problematic has been detected in py-lmdb 0.97. The affected element is the function mdb_env_open2. Performing a manipulation of the argument size as part of Header results in divide by zero.
This vulnerability is known as CVE-2019-16228. Remote exploitation of the attack is possible. No exploit is available.
Details
A vulnerability was found in py-lmdb 0.97. It has been classified as problematic. This affects the function mdb_env_open2. The manipulation of the argument size as part of a Header leads to a divide by zero vulnerability. CWE is classifying the issue as CWE-369. The product divides a value by zero. This is going to have an impact on availability. The summary by CVE is:
An issue was discovered in py-lmdb 0.97. There is a divide-by-zero error in the function mdb_env_open2 if mdb_env_read_header obtains a zero value for a certain size field.
The weakness was published 09/11/2019. This vulnerability is uniquely identified as CVE-2019-16228 since 09/11/2019. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. Technical details of the vulnerability are known, but there is no available exploit. The attack technique deployed by this issue is T1499 according to MITRE ATT&CK.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Similar entries are available at VDB-141674, VDB-141673, VDB-141672 and VDB-141671. Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 6.4VulDB Meta Temp Score: 6.4
VulDB Base Score: 5.3
VulDB Temp Score: 5.3
VulDB Vector: 🔍
VulDB Reliability: 🔍
NVD Base Score: 7.5
NVD Vector: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
|---|---|---|---|---|---|
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
|---|---|---|---|---|---|
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
NVD Base Score: 🔍
Exploiting
Class: Divide by zeroCWE: CWE-369 / CWE-404
CAPEC: 🔍
ATT&CK: 🔍
Physical: No
Local: No
Remote: Yes
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
| 0-Day | Unlock | Unlock | Unlock | Unlock |
|---|---|---|---|---|
| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔍
Timeline
09/11/2019 🔍09/11/2019 🔍
09/12/2019 🔍
12/19/2023 🔍
Sources
Advisory: github.comStatus: Not defined
CVE: CVE-2019-16228 (🔍)
GCVE (CVE): GCVE-0-2019-16228
GCVE (VulDB): GCVE-100-141675
See also: 🔍
Entry
Created: 09/12/2019 08:31Updated: 12/19/2023 11:55
Changes: 09/12/2019 08:31 (37), 08/21/2020 09:38 (17), 12/19/2023 11:55 (3)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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