Irene Sciriha

26 papers Journal 26
YearRankTypeTitle / Venue / Authors
2023 J jnl
Discret. Math.
Irene Sciriha, Zoran Stanic
2023 J jnl
Discuss. Math. Graph Theory
Irene Sciriha, Luke Collins
2022 J jnl
Discuss. Math. Graph Theory
Nino Basic, Patrick W. Fowler, Tomaz Pisanski, Irene Sciriha
2021 J jnl
Symmetry
Irene Sciriha
2021 J jnl
J. Comb. Optim.
Irene Sciriha, Xandru Mifsud, James L. Borg
2020 J jnl
Discuss. Math. Graph Theory
Patrick W. Fowler, John Baptist Gauci, Jan Goedgebeur, Tomaz Pisanski, Irene Sciriha
2020 J jnl
Discuss. Math. Graph Theory
Johann A. Briffa, Irene Sciriha
2019 J jnl
CoRR
Patrick W. Fowler, John Baptist Gauci, Jan Goedgebeur, Tomaz Pisanski, Irene Sciriha
2019 J jnl
CoRR
Johann A. Briffa, Irene Sciriha
2019 J jnl
Discret. Appl. Math.
Irene Sciriha, Josef Lauri, John Baptist Gauci, Peter Borg
2019 J jnl
Ars Math. Contemp.
Irene Sciriha, Didar A. Ali, John Baptist Gauci, Khidir Sharaf
2019 J jnl
Discret. Appl. Math.
Irene Sciriha, Luke Collins
2018 J jnl
CoRR
Irene Sciriha, Johann A. Briffa, Mark Debono
2018 J jnl
Discret. Appl. Math.
Irene Sciriha, Johann A. Briffa, Mark Debono
2017 J jnl
Ars Math. Contemp.
Patrick W. Fowler, Barry T. Pickup, Irene Sciriha, Martha Borg
2016 J jnl
Ars Math. Contemp.
Alexander Farrugia, John Baptist Gauci, Irene Sciriha
2016 J jnl
Ars Math. Contemp.
Irene Sciriha, Alexander Farrugia
2016 J jnl
Discret. Appl. Math.
Alexander Farrugia, John Baptist Gauci, Irene Sciriha
2013 J jnl
Ars Math. Contemp.
Irene Sciriha, Mark Debono, Marta Borg, Patrick W. Fowler, Barry T. Pickup
2009 J jnl
Ars Math. Contemp.
Irene Sciriha
2008 J jnl
Ars Math. Contemp.
Irene Sciriha
2008 J jnl
Discret. Math.
Irene Sciriha, Patrick W. Fowler
2007 J jnl
J. Chem. Inf. Model.
Irene Sciriha, Patrick W. Fowler
2001 J jnl
Discret. Math.
Ivan Gutman, Irene Sciriha
1998 J jnl
Discret. Math.
Irene Sciriha
1997 J jnl
Discret. Math.
Irene Sciriha, Stanley Fiorini
redb/extractors/js_extractors/js_content.py
← Index redb/extractors/js_extractors/js_content.py python
"""Persists raw + normalised text into the generic `code_text_content` table.

Reads the raw source and the deobfuscation result directly from the shared
JSContext so no extra compute happens here — both values are computed once
per sample (the source at JSContext construction, the deobfuscation lazily
on first access) and reused by any extractor that needs them.

`text_normalized` is left NULL when the deobfuscation pass produced no
output, so analysts can distinguish "we tried and got nothing" from
"normalisation succeeded".
"""

import inspect
from datetime import datetime, timezone
from typing import Any

from redb.extractors.enum import Tag
from redb.extractors.js_extractor import JSExtractor


class JSContentExtractor(JSExtractor):

    def __init__(
        self, filepath, log, exporters=None, index_prefix=None,
        known_benign=False, known_malicious=False, source=None, context=None,
    ):
        super().__init__(
            filepath, log, exporters, index_prefix,
            known_benign, known_malicious, source, context=context,
        )
        self.content_row = None
        self.log.debug(inspect.currentframe().f_code.co_name)

    def tag(self):
        return Tag.JS_CONTENT.value

    def extract(self):
        src = self.js_source
        if not src:
            return None

        deobfuscated, normalizer_used = self._context.deobfuscated

        self.content_row = {
            "content_type": self._context.content_type,
            "text_raw": src,
            "text_normalized": deobfuscated,  # may be None
            "normalizer_used": normalizer_used,  # may be None
        }
        return self.content_row

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type != "ClickHouseExporter":
            return None
        if not self.content_row:
            return None

        r = self.content_row
        data = [[
            self.sha256,
            r["content_type"],
            r["text_raw"],
            r["text_normalized"],
            r["normalizer_used"],
            datetime.now(timezone.utc),
        ]]

        column_names = [
            "sha256",
            "content_type",
            "text_raw",
            "text_normalized",
            "normalizer_used",
            "analysis_date",
        ]

        column_type_names = [
            "FixedString(64)",
            "LowCardinality(String)",
            "String",
            "Nullable(String)",
            "Nullable(String)",
            "DateTime64(3, 'UTC')",
        ]

        return (data, column_names, column_type_names)

    def get_clickhouse_table(self) -> str:
        return "code_text_content"