chore(findings): aiml/jupyter/jlab-nlp
Summary
aiml/jupyter/jlab-nlp has 56 new findings discovered during continuous monitoring.
| id | source | severity | package |
|---|---|---|---|
| CVE-2022-35256 | Anchore CVE | Medium | nodejs-full-i18n-1:16.17.1-1.module+el8.6.0+16848+a483195a |
| CVE-2022-35256 | Anchore CVE | Medium | nodejs-docs-1:16.17.1-1.module+el8.6.0+16848+a483195a |
| GHSA-368v-7v32-52fx | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-mv77-9g28-cwg3 | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-3352 | Anchore CVE | Low | vim-enhanced-2:8.0.1763-19.el8_6.4 |
| CVE-2022-41858 | Anchore CVE | Medium | kernel-headers-4.18.0-425.3.1.el8 |
| CVE-2022-3566 | Anchore CVE | Medium | kernel-headers-4.18.0-425.3.1.el8 |
| GHSA-frqp-wp83-qggv | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-3352 | Anchore CVE | Low | vim-minimal-2:8.0.1763-19.el8_6.4 |
| GHSA-gq2j-cr96-gvqx | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-66vq-54fq-6jvv | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-43945 | Anchore CVE | High | kernel-headers-4.18.0-425.3.1.el8 |
| GHSA-rjx6-v474-2ch9 | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-35255 | Anchore CVE | High | nodejs-1:16.17.1-1.module+el8.6.0+16848+a483195a |
| GHSA-xvwp-h6jv-7472 | Anchore CVE | High | tensorflow-2.10.0 |
| CVE-2022-3625 | Anchore CVE | Medium | kernel-headers-4.18.0-425.3.1.el8 |
| CVE-2022-42895 | Anchore CVE | Medium | kernel-headers-4.18.0-425.3.1.el8 |
| GHSA-hq7g-wwwp-q46h | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-xxcj-rhqg-m46g | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-3352 | Anchore CVE | Low | vim-filesystem-2:8.0.1763-19.el8_6.4 |
| GHSA-w58w-79xv-6vcj | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-f2w8-jw48-fr7j | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-35256 | Anchore CVE | Medium | nodejs-1:16.17.1-1.module+el8.6.0+16848+a483195a |
| GHSA-8fvv-46hw-vpg3 | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-4129 | Anchore CVE | Medium | kernel-headers-4.18.0-425.3.1.el8 |
| CVE-2022-23824 | Anchore CVE | Medium | kernel-headers-4.18.0-425.3.1.el8 |
| GHSA-pf36-r9c6-h97j | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-45061 | Anchore CVE | High | python-3.8.13 |
| CVE-2022-3352 | Anchore CVE | Low | vim-common-2:8.0.1763-19.el8_6.4 |
| GHSA-jq6x-99hj-q636 | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-67pf-62xr-q35m | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-xf83-q765-xm6m | Anchore CVE | Low | tensorflow-2.10.0 |
| GHSA-54pp-c6pp-7fpx | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-cqvq-fvhr-v6hc | Anchore CVE | Low | tensorflow-2.10.0 |
| CVE-2022-3567 | Anchore CVE | Medium | kernel-headers-4.18.0-425.3.1.el8 |
| CVE-2022-35255 | Anchore CVE | High | nodejs-docs-1:16.17.1-1.module+el8.6.0+16848+a483195a |
| CVE-2022-41222 | Anchore CVE | High | kernel-headers-4.18.0-425.3.1.el8 |
| CVE-2022-3903 | Anchore CVE | Low | kernel-headers-4.18.0-425.3.1.el8 |
| CVE-2022-35255 | Anchore CVE | High | npm-1:8.15.0-1.16.17.1.1.module+el8.6.0+16848+a483195a |
| GHSA-27rc-728f-x5w2 | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-g9fm-r5mm-rf9f | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-42896 | Anchore CVE | Medium | kernel-headers-4.18.0-425.3.1.el8 |
| CVE-2022-35255 | Anchore CVE | High | nodejs-full-i18n-1:16.17.1-1.module+el8.6.0+16848+a483195a |
| GHSA-8w5g-3wcv-9g2j | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-cg88-rpvp-cjv5 | Anchore CVE | High | tensorflow-2.10.0 |
| CVE-2022-35256 | Anchore CVE | Medium | npm-1:8.15.0-1.16.17.1.1.module+el8.6.0+16848+a483195a |
| GHSA-h246-cgh4-7475 | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-6x99-gv2v-q76v | Anchore CVE | Medium | tensorflow-2.10.0 |
| GHSA-rmg2-f698-wq35 | Anchore CVE | Medium | tensorflow-2.10.0 |
| CVE-2022-45939 | Twistlock CVE | Medium | emacs-filesystem-26.1-7.el8 |
| CVE-2022-4141 | Twistlock CVE | Low | vim-common-8.0.1763-19.el8_6.4 |
| CVE-2022-4141 | Twistlock CVE | Low | vim-filesystem-8.0.1763-19.el8_6.4 |
| CVE-2022-4141 | Twistlock CVE | Low | vim-minimal-8.0.1763-19.el8_6.4 |
| CVE-2022-4141 | Twistlock CVE | Low | vim-enhanced-8.0.1763-19.el8_6.4 |
| CVE-2022-45939 | Anchore CVE | Medium | emacs-filesystem-1:26.1-7.el8 |
| CVE-2022-4139 | Anchore CVE | High | kernel-headers-4.18.0-425.3.1.el8 |
VAT: https://vat.dso.mil/vat/image?imageName=aiml/jupyter/jlab-nlp&tag=3.4.4&branch=master
More information can be found in the failed pipeline located here: https://repo1.dso.mil/dsop/aiml/jupyter/jlab-nlp/-/jobs/16294129
Tasks
Contributor:
-
Provide justifications for findings in the VAT (docs) -
Apply the ~"Hardening::Approval" label to this issue and wait for feedback
Iron Bank:
-
Review findings and justifications -
Send approval request to Authorizing Official -
Close issue after approval from Authorizing Official
Note: If the above approval process is rejected for any reason, the
Approvallabel will be removed and the issue will be sent back toOpen. Any comments will be listed in this issue for you to address. Once they have been addressed, you must re-add theApprovallabel.
Questions?
Contact the Iron Bank team by commenting on this issue with your questions or concerns. If you do not receive a response, add /cc @ironbank-notifications/onboarding.
Additionally, Iron Bank hosts an AMA working session every Wednesday from 1630-1730EST to answer questions.
Edited by Ghost User