PT-Guard: Integrity-Protected Page Tables to Defend Against Breakthrough Rowhammer Attacks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Page tables enforce process isolation in systems. Rowhammer attacks break process isolation by flipping bits in DRAM to tamper page tables and achieving privilege escalation. Moreover, new Rowhammer attacks break existing mitigations. We seek to protect systems against such breakthrough attacks. We present PT-Guard, an integrity protection mechanism for page tables. PT-Guard uses unused bits in Page Table Entries (PTE) to embed a Message Authentication Code (MAC) for the PTE cacheline without any storage overhead. These unused bits arise from PTEs supporting petabytes of physical memory while systems targeted by Rowhammer use at-most terabytes of mem-ory. By storing and verifying MACs for PTEs, PT-Guard detects arbitrary bit-flips in PTEs. Moreover, PT-Guard also provides best-effort correction of faulty-PTEs leveraging value locality. PT-Guard protects page tables from breakthrough Rowhammer attacks with negligible hardware changes, no DRAM storage, <72 bytes of SRAM, 1.3% slowdown, and no software changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it